| id,role,type,job_desc,year,qualification,experience,tech_skills,soft_skills
|
| 5,AI Engineer,Junior,"AI/ML models, Python, Core ML concepts, ML framework (Scikit‑learn/TensorFlow/PyTorch), MLOps, SQL/NoSQL, Messaging/queue systems |
| 0–1 year of experience as an AI/ML Engineer, Data Scientist, or similar role, or strong academic/personal projects in AI/ML. |
| Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or equivalent practical experience. |
| Solid Python skills for data processing and model development. |
| Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, overfitting, etc. |
| Experience with at least one ML framework (e.g., scikit‑learn, TensorFlow, or PyTorch). |
| Ability to work with databases (SQL/NoSQL) and basic messaging/queue systems to move data in and out of models. |
| Strong problem‑solving mindset, eagerness to learn, and comfort working in a fast‑moving environment. |
| Good communication skills and willingness to collaborate in a team and with non‑technical stakeholders.",2026,Bachelors,0-1,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, MLOps, Model Training, Feature Engineering","Communication, Problem Solving"
|
| 6,AI Engineer,Junior,"4–5 years of proven development experience in AI/ML for embedded device |
| Strong expertise in deep learning frameworks (TensorFlow, PyTorch, ONNX, TensorRT). |
| Expert proficiency with open-source infrastructure tools like llama.cpp, vLLM, Ollama, and NVIDIA Triton Inference Server for local model serving, high-throughput inference, and quantization. |
| Hands-on experience building complex, stateful workflows and tracking applications using LangChain, LangGraph, and Langfuse. |
| Expertise in selecting, benchmarking, and adapting state-of-the-art open-source architectures (such as Llama 3, gemma, Qwen, and Kimi) for enterprise tasks |
| Practical experience with edge/embedded AI (NVIDIA Jetson, Qualcomm, ARM). |
| Proficiency in NLP / Conversational AI / Speech interfaces ( ASR, TTS ) |
| Solid programming skills in Python and C++/Java for optimization and integration. |
| Solid understanding of application development in embedded Linux / Android |
| Familiarity with automotive standards, protocols such as CAN |
| Familiarity with cloud ML services like AWS SageMaker or Azure ML |
| Good communication skills and great team spirit. |
| Experience working with embedded Linux, Automotive Android |
| Knowledge of vehicle data interfaces (CAN, OBD-II, sensors). |
| Exposure to LLMOps & MLOps pipelines and cloud platforms (AWS/GCP/Azure). |
| ",2026,Bachelors,5-10,"Python, C++, Java, TensorFlow/PyTorch, vLLM, Ollama, LangChain, LangGraph, NLP, AWS/Azure, MLOps","Communication, Problem Solving"
|
| 8,AI Engineer,Junior,"Proficiency in C/C++ and python programming |
| Hands-on experience in deploying AI models on embedded platforms. |
| Experience working with MCU, bare-metal, RTOS and Edge AI/ML applications |
| Experience working with multi-core, multi-threaded applications, IPC and task scheduling |
| Strong knowledge in board bring-up and interfaces such as OSPI, GPIO, UART, SRAM, SDRAM etc. |
| Good debugging and problem-solving skills. |
| Experience in various profiling tools, and proficiency in identifying deviations from expected behaviour and finding their root causes |
| Ability to use Hardware test equipment: Joulescope, oscilloscope, logic analyzer and JTAG |
| Understanding of system constraints like memory, compute, and power on edge devices. |
| Good communication skills for clearly communicating ideas and concepts to team/customer",2026,Bachelors,0-1,"Python, C, C++, Sytem Design, Model Evaluation","Communication, Problem Solving"
|
| 14,AI Engineer,Junior,"Basic understanding of AI, Machine Learning, or Automation concepts |
| Familiarity with Python / APIs / No-code & Low-code tools (preferred but not mandatory |
| Good problem-solving and logical thinking skills |
| Willingness to learn and adapt quickly |
| Good communication skills",2026,Bachelors,0-1,"Python, ML, APIs","Communication, Problem Solving"
|
| 16,AI Engineer,Junior,"Docker / Containerization |
| AWS / Azure / GCP exposure |
| AI Agent workflow understanding |
| ML fundamentals |
| Enterprise AI integration experience",2026,Bachelors,0-1,"Python, ML, Docker, AWS/Azure, ","Communication, Problem Solving"
|
| 17,AI Engineer,Junior,"1+ years of experience in AI, LLMs, automation, or related systems |
| Strong Python programming skills with experience in APIs and backend integration |
| Hands-on experience in prompt engineering, LLM orchestration, and evaluation |
| Familiarity with LangChain, embeddings, vector databases, and RAG systems |
| Strong problem-solving skills with ability to build and ship MVPs quickly |
| Passion for AI, automation, and real-world product development |
| Strong ownership mindset |
| Ability to work in fast-paced startup environments |
| Good understanding of AI product thinking and user experience |
| Strong communication and collaboration skills |
| ",2026,Bachelors,1-5,"Python, APIs, LLMs, Prompt Engineering, LangChain, LlamaIndex, LangGraph, CrewAI, AutoGen, Anthropic /OpenAI SDKs, MCP, VectorDB, n8n, RAG, Agents","Communication, Problem Solving, Ownership"
|
| 18,AI Developer,Junior,"Strong Python programming |
| Experience with FastAPI, Flask, or similar backend frameworks |
| Understanding of REST APIs |
| Familiarity with cloud platforms (AWS) - Exposure to services like S3, EC2, Lambda, or API Gateway is a plus |
| Experience working with AI/LLM APIs |
| Knowledge of data processing (CSV, JSON, Pandas) |
| Familiarity with Git and version control |
| Basic understanding of Docker and cloud deployment |
| Experience with RAG pipelines |
| Experience with vector databases (Pinecone, Weaviate, FAISS, etc.) |
| Experience parsing PDF documents |
| Knowledge of LangChain or LlamaIndex |
| Basic frontend knowledge (React / simple JS) |
| ",2026,Bachelors,0-1,"Python, React, Javascript, APIs, AWS/Azure, LLMs, Git, Docker, RAG, VectorDB, LangChain","Communication, Problem Solving"
|
| 19,AI Engineer,Junior,"Degree in Computer Science, AI, or a related field (or equivalent practical experience).Strong command of Python, JavaScript, or other common programming languages.Hands-on experience with prompt engineering, LLMs, and AI-assisted coding tools.Familiarity with cloud-based IDEs, version control (e.g., Git), and API integrations.Excellent communication skills for client-facing interactions (live and written).Comfortable working independently in a remote, fast-paced environment.",2026,Bachelors,0-1,"Python, Javascript, LLMs, Prompt Engineering, APIs","Communication, Problem Solving"
|
| 22,AI Engineer,Junior,"Strong programming skills in Python. |
| Experience with LLM architectures, prompt engineering, and RAG systems. |
| Familiarity with deep learning frameworks such as PyTorch or TensorFlow. |
| Experience with vector databases like Pinecone, Weaviate, or Milvus. |
| Azure expertise as must have, while AWS & GCP",2026,Bachelors,0-1,"Python, LLMs, Prompt Engineering, RAG, TensorFlow/PyTorch, VectorDB, AWS/Azure","Communication, Problem Solving"
|
| 26,AI Engineer,Junior,"Strong hands-on experience in Python programming |
| Ability to code independently without relying on AI coding tools |
| Basic understanding of AI/ML concepts and frameworks |
| Knowledge of APIs, data structures, and problem-solving techniques |
| Good communication and collaboration skills |
| Self-motivated with a strong learning attitude |
| Familiarity with Generative AI, LLMs, or automation tools |
| Understanding of libraries such as Pandas, NumPy, Scikit-learn, or FastAPI |
| Exposure to Git/GitHub and cloud platforms is a plus |
| Bachelor’s degree in Computer Science, IT, or related field |
| Candidates with internship/project experience in AI/ML are encouraged to apply |
| ",2026,Bachelors,0-1,"Python, APIs, GenAI, LLMs, Pandas, NumPy, Scikit-Learn, Git, Github","Communication, Problem Solving"
|
| 35,AI Developer,Junior,"Strong foundation in Java, React, NodeJS, Python, SQL, and Excel Basic understanding of data structures, databases, and algorithms Exposure to pandas, NumPy, PySpark, scikit-learn, GenAI, Agentic AI or TensorFlow is a plus Familiarity with BI tools (e.g., Power BI, Tableau) or cloud platforms (e.g., AWS, GCP) is desirable Knowledge of version control (Git) is an advantage Soft Skills Curiosity and a passion for data-driven problem solving Strong analytical and logical thinking Good communication and collaboration skills Willingness to learn in a fast-paced environment Ability to break down complex problems and document clearly Preferred (Good to Have, Not Mandatory) Internship or academic project in data analytics, machine learning, or database systems Participation in hackathons, coding contests, or Kaggle competitions Exposure to Agile or collaborative tools like JIRA, Confluence ",2026,Bachelors,0-1,"Java, React, NodeJS, Python, SQL, Excel, Pandas, NumPy, Scikit-Learn, GenAI, TensorFlow/PyTorch, Git, Github, AWS/Azure","Problem Solving, Strong analytical, logical thinking, Communication "
|
| 36,AI Engineer,Junior,"Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. |
| Experience: 0 to 1 yr / 2025 Passouts / upcoming 2026 passouts Preferred Proficiency in Python programming with a strong grasp of core concepts. |
| Basic Data Structures and Algorithms: Familiarity with common data structures (lists, dictionaries, tuples) and basic algorithms (sorting, searching) is advantageous. |
| Problem-Solving Skills: Ability to analyse and solve programming problems using Python. |
| Understanding of Object-Oriented Programming (OOP): Basic understanding of OOP principles like classes, objects, inheritance, and encapsulation |
| Basic knowledge in Data Science including but not limited to ETL, EDA, Data Processing, Visualization etc. |
| Familiarity with machine learning and deep learning models (e.g., TensorFlow, Keras, PyTorch). |
| Experience working with SQL DMBS like PostgreSQL is a plus. |
| Basic understanding of Natural Language Processing (NLP) concepts |
| Knowledge of Python frameworks like Django |
| Familiarity with Jira and Agile methodology will be an added advantage. |
| Certification or experience in data analysis, data mining, and statistical modelling is an added advantage |
| Strong knowledge of statistical concepts and techniques. |
| Knowledge in data visualization tools (Tableau, Power BI, etc.) and SQL. |
| Excellent problem-solving and analytical skills. |
| Strong communication and presentation skills. |
| Certification in Data Science is an added advantage. |
| ",2026,Bachelors,0-1,"Python, TensorFlow/PyTorch, SQL, NLP, PowerBI","Communication, Problem Solving"
|
| 37,AI Engineer,Junior,"• 0–1 year of experience as an AI/ML Engineer, Data Scientist, or similar role, or strong academic/personal projects in AI/ML. |
| • Bachelor’s degree in Computer Science, Engineering, Data Science, Mathematics, or equivalent practical experience. |
| • Solid Python skills for data processing and model development. |
| • Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, overfitting, etc. |
| • Experience with at least one ML framework (e.g., scikit‑learn, TensorFlow, or PyTorch). |
| • Ability to work with databases (SQL/NoSQL) and basic messaging/queue systems to move data in and out of models. |
| • Strong problem‑solving mindset, eagerness to learn, and comfort working in a fast‑moving environment. |
| • Good communication skills and willingness to collaborate in a team and with non‑technical stakeholders. |
| • Experience running or fine‑tuning local LLMs (e.g., via Ollama) or other open‑source models. |
| • Exposure to workflow automation, or operations-heavy domains. |
| • Familiarity with basic MLOps tools (MLflow, DVC, Weights & Biases) and containerization (Docker). |
| • Basic knowledge of any cloud platform (AWS, Azure, GCP) for deploying services. |
| • Experience integrating ML models into web backends (REST APIs, microservices, Node.js/Next.js). |
| • Understanding of vector databases or simple retrieval/RAG systems for LLM-based solutions. |
| • Awareness of ethical AI, bias, and privacy considerations. |
| ",2026,Bachelors,0-1,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, MLOps, Model Training, Feature Engineering, RAG, AWS/Azure, LLMs","Communication, Problem Solving"
|
| 43,AI Engineer,Junior,"• Strong programming skills in Python. |
| • Understanding of Data Structures and Algorithms. |
| • Knowledge of Machine Learning fundamentals. |
| • Understanding of Natural Language Processing (NLP) concepts: |
| • Tokenization |
| • Embeddings |
| • Text Classification |
| • Named Entity Recognition (NER) |
| • Semantic Search |
| • Transformer Models |
| • Understanding of Generative AI concepts: |
| • Large Language Models (LLMs) |
| • Prompt Engineering |
| • RAG (Retrieval-Augmented Generation) |
| • Fine-tuning concepts |
| • AI Agent fundamentals |
| • Familiarity with AI/ML frameworks: |
| • PyTorch or TensorFlow |
| • Hugging Face Transformers |
| • LangChain, LlamaIndex, or similar frameworks |
| • Understanding of model deployment and serving concepts. |
| • Familiarity with: |
| • Docker |
| • Git/GitHub |
| • CI/CD concepts |
| • Kubernetes (basic understanding) |
| • ML experiment tracking tools (MLflow, Weights & Biases, etc.) |
| • Basic knowledge of SQL databases. |
| • Familiarity with vector databases such as Pinecone, Weaviate, Qdrant, or ChromaDB. |
| • Understanding of REST APIs and FastAPI. |
| • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field. |
| • Hands-on academic projects, internships, or personal projects in AI/ML. |
| • Experience building chatbots, AI assistants, or NLP applications. |
| • Contributions to open-source AI projects are a plus. |
| • Familiarity with cloud platforms such as AWS, GCP, or Azure. |
| • Strong problem-solving and analytical skills. |
| • Passion for AI, Machine Learning, and emerging technologies. |
| • Curiosity to learn and experiment with new AI frameworks and tools. |
| • Good communication and teamwork skills. |
| • Ability to work in a fast-paced, collaborative environment",2026,Bachelors,0-1,"Python, ML, NLP, MLOPS, Docker, GenAI, RAG, VectorDB, Agents, Prompt Engineering, TensorFlow/PyTorch, LangChain, LangGraph, Hugging Face, CI/CD, Git, Github, Kubernetes, MLflow, APIs, AWS/Azure","Communication, Problem Solving, Analytical Skills"
|
| 55,AI Engineer,Junior,"• Strong understanding of RAG architecture — document chunking, embedding, retrieval, reranking, and synthesis. |
| • Proficiency in Python, including libraries like Pandas,Numpy, and Scikit-learn. |
| • Experience withFastAPIor Flask for microservice and API development. |
| • Hands-on withLangGraph,LangChain, or MCP for multi-agent orchestration. |
| • Familiarity with vector databases (FAISS,ChromaDB,Weaviate, Elasticsearch). |
| • Good Working knowledge of ML/DL frameworks (TensorFlow,PyTorch). |
| • Understanding of model serving via REST APIs, batch jobs, or pipelines. |
| • Exposure to containerization (Docker) and scalable architecture patterns. |
| • Familiarity with Git,MLflow, or DVC for versioning, tracking, and collaboration. |
| • Awareness of cloud AI/ML services (Azure ML, AWS SageMaker, GCP Vertex AI). |
| • Understanding of prompt evaluation, retrieval accuracy metrics, and contextual reasoning benchmarks. |
| • Curiosity to explore Agentic AI frameworks and autonomous reasoning systems. |
| • Analytical mindset with a focus on debugging, optimization, and scalability. |
| • Strong communication and documentation skills for collaborative workflows. |
| • Innovative and research-driven approach toward new AI architectures. |
| • Eagerness to experiment, iterate, and learn from production-level systems. ",2026,Bachelors,0-1,"Python, ML, RAG, APIs, LangChain, LangGraph, MCP, TensorFlow/PyTorch, Docker, Git, Github, MLflow, AWS/Azure","Communication, Problem Solving"
|
| 57,AI Engineer,Junior,"Bachelor's degree in a relevant field such as Computer Science, Data Science, or a related field |
| 1–2 years of professional experience building or supporting software or AI-driven systems in a work environment (internships and co-ops included) |
| Hands-on experience working with LLM-based applications or agentic workflows in a professional or production setting |
| Strong programming skills, including experience with: Python (preferred), Java (optional), Scala (optional) |
| Experience working with APIs and backend development frameworks (e.g., Flask, FastAPI) in a job setting |
| Familiarity with LLM frameworks or platforms (e.g., LangChain, LangGraph, OpenAI, Gemini) |
| Basic SQL skills and experience working with structured and unstructured data |
| Experience contributing to applications or pipelines deployed in cloud environments such as GCP, AWS, or Azure |
| Understanding of data pipelines, APIs, and system integrations |
| Excellent communication and collaboration skills in a team-based environment |
| Ability to work independently and manage multiple tasks and priorities",2026,Bachelors,0-1,"Python, LLMs, Java, LangChain, LangGraph, OpenAI, SQL, AWS/Azure, ","Communication, Problem Solving"
|
| 58,AI Engineer,Junior,"- Solid Python skills (async/await, type hints, standard library) |
| - Experience building or consuming REST APIs (FastAPI, Flask, or Django) |
| - Exposure to at least one LLM provider API |
| - Comfort navigating and contributing to an existing codebase |
| - Git workflow (branches, PRs) |
| - MongoDB or PostgreSQL |
| - Docker, AWS |
| - pytest or any testing framework |
| - Experience with LiteLLM, LangChain, or similar |
| - AI coding tools (Cursor, Copilot, Claude) |
| Interested Candidates can drop their cv at recruitment@qwikgig.com or can reach us out at |
| • LLM APIs: 1 year (Required) |
| • Python: 1 year (Required) |
| • Fast API: 1 year (Required) |
| • Flask: 1 year (Required) |
| • Django: 1 year (Required) ",2026,Bachelors,0-1,"Python, APIs, LLMs, Git, Github, VectorDB, SQL, Docker, AWS/Azure, LangChain, LangGraph, Django","Communication, Problem Solving"
|
| 59,AI Engineer,Junior,"Python as primary language. |
| Microsoft Azure required as the primary cloud platform. |
| Hands-on experience building with Azure AI Foundry. |
| Claude Code experience and expertise required, including hands-on development of skills and plugins on the platform. This is non-negotiable for the role. |
| LangGraph experience required. Demonstrated ability to design state graphs, conditional edges, and multi-agent compositions. |
| Model Context Protocol experience required. Comfortable designing tool calls and building protocol wrappers. |
| Agentic pair programming with generative AI as the primary working mode. Prior experience is required. |
| Pydantic for data validation and structured outputs across agent systems and APIs. |
| SQL proficiency and PostgreSQL experience. |
| Vector database experience (pgvector, Azure AI Search, or similar). |
| Familiarity with modern data platforms such as Snowflake and Databricks. |
| Multi-step agent systems with proper evaluation and validation. |
| Strong fluency across modern frontier language models such as the GPT, Claude, and Gemini model families. Model selection is driven by the requirements of each task and the practical considerations of cost. |
| The discipline to choose mature, proven frameworks for AI engineering work. Technical decisions are grounded in clear engineering justification and supported by data. |
| Docker and containerization for development and deployment workflows. |
| FastAPI or equivalent web frameworks for building APIs and backend services. |
| Working knowledge of GitHub workflows, code review discipline, and infrastructure-as-code patterns. |
| Although Microsoft Azure is the primary platform, Google Cloud Platform experience is also valuable and applicable to the practice's work. |
| Familiarity with Azure Container Apps, Azure Kubernetes Services, or similar container orchestration platforms. |
| Familiarity with Apache Software Foundation tools such as Apache Airflow, Apache Kafka, and Apache Flink. |
| Experience with LangChain, PyTorch, or other AI and machine learning frameworks. |
| CrewAI or other multi-agent frameworks. |
| LlamaIndex for RAG and data ingestion workflows. |
| Celery and Redis for background task processing and caching. |
| Familiarity with A2A (Agent-to-Agent) protocol for inter-agent communication. |
| Experience with modern natural language processing tools, including embedding models and entity recognition. |
| Familiarity with vision-language model integration for multi-modal AI use cases. |
| Experience working in regulated markets, including the compliance and risk-management disciplines such environments require. |
| Playwright for end-to-end testing automation. |
| Familiarity with hybrid architectures that integrate deterministic and generative AI techniques. ",2026,Bachelors,0-1,"Python, AWS/Azure, LangChain, LangGraph, APIs, MCP, SQL, VectorDB,n8n, LLMs, CrewAI, TensorFlow/Pytorch, Agents, RAG","Communication, Problem Solving"
|
| 62,AI Engineer,Junior,"4 to 5 years of Python engineering or a CS degree with strong applied ML/NLP track record |
| Hands-on with LLMs, prompt engineering, RAG architectures, and vector databases (Pinecone, Azure AI Search, or equivalent |
| Experience with Azure OpenAI Service, LangChain, or similar orchestration frameworks |
| Comfort working within a Microsoft Azure cloud environment |
| Strong understanding of HIPAA/PIPEDA data handling — or fast learner in regulated environments |
| Production mindset — you’ve shipped models, not just notebooks |
| Healthcare SaaS or healthtech experience |
| Experience with voice AI or conversational AI |
| Familiarity with .NET8 or React integration patterns for AI services ",2026,Bachelors,0-1,"Python, Ml, NLP, LLMs, Prompt Engineering, RAG, VectorDB, LangChain, OpenAI, AWS/Azure, .NET, React","Communication, Problem Solving"
|
| 63,AI Engineer,Junior,"• Strong foundation in Computer Science and Software Development, including algorithms, data structures, version control, and production-grade coding practices. |
| • Hands-on experience with Neural Networks and Pattern Recognition, including training, tuning, and deploying deep learning models for classification, prediction, or recommendation tasks. |
| • Practical expertise in Natural Language Processing (NLP), such as text classification, information extraction, embeddings, and working with modern NLP frameworks or large language models. |
| • Proficiency with common AI/ML tools and frameworks (e.g., Python, PyTorch or TensorFlow, scikit-learn, Docker, cloud platforms such as AWS, GCP, or Azure). |
| • Bachelor’s or higher degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent practical experience. |
| • Experience building and deploying models into production environments, including working with APIs, microservices, and CI/CD pipelines. |
| • Strong analytical and problem-solving skills, with the ability to translate business requirements into robust AI solutions. |
| • Effective written and verbal communication skills, and the ability to collaborate with distributed, cross-functional teams across time zones. |
| • Familiarity with MLOps practices, monitoring and observability for models, and responsible AI considerations (fairness, bias, and explainability) is a plus. ",2026,Bachelors,0-1,"Python, NLP, Python, TensorFlow/PyTorch, Scikit-Learn, Docker, AWS/Azure, API, CI/CD, MLOps","Communication, Problem Solving"
|
| 65,AI Engineer,Junior,"• You have shipped multi-agent systems in production — not prototypes, not demos. Real users, real scale, real failure modes. |
| • You have deep, hands-on experience with both vector databases and knowledge graphs, and critically, with combining them in hybrid retrieval architectures. |
| • You understand orchestration frameworks (LangGraph, CrewAI, AutoGen, or equivalent) well enough to know when not to use one. |
| • You can design retrieval pipelines that blend semantic search, graph traversal, and temporal signals — the kind of system that models like Ebbinghaus forgetting curves and Zeigarnik effects demand. |
| • You have practical experience with protocol-level integration work connecting AI agents to external services and data sources. |
| • You communicate architecturally — you can draw a system on a whiteboard and make a room of senior engineers and investors understand why it matters. |
| • Background in cognitive science, computational neuroscience, or memory systems research — even informally. |
| • Experience scaling AI systems in B2C (consumer-grade latency, UX sensitivity, personalization at scale). |
| • Track record mentoring engineers and building AI-capable teams from strong traditional engineering foundations. |
| • Contributions to open-source AI/ML infrastructure projects. ",2026,Bachelors,0-1,"Python, VectorDB, LangGraph, CrewAI, AutoGen, ML","Communication, Problem Solving"
|
| 68,AI Engineer,Junior,"Bachelor's degree in a relevant field such as Computer Science, Data Science, or a related field |
| 1–2 years of professional experience building or supporting software or AI-driven systems in a work environment (internships and co-ops included) |
| Hands-on experience working with LLM-based applications or agentic workflows in a professional or production setting |
| Strong programming skills, including experience with: Python (preferred), Java (optional), Scala (optional) |
| Experience working with APIs and backend development frameworks (e.g., Flask, FastAPI) in a job setting |
| Familiarity with LLM frameworks or platforms (e.g., LangChain, LangGraph, OpenAI, Gemini) |
| Basic SQL skills and experience working with structured and unstructured data |
| Experience contributing to applications or pipelines deployed in cloud environments such as GCP, AWS, or Azure |
| Understanding of data pipelines, APIs, and system integrations |
| Excellent communication and collaboration skills in a team-based environment |
| Ability to work independently and manage multiple tasks and priorities ",2026,Bachelors,0-1,"Python, LLMs, Agents, Python, Java, APIs, LangChain, LangGraph, OpenAI, SQL, AWS/Azure","Communication, Problem Solving"
|
| 71,AI Engineer,Junior,"• Proficiency in Pattern Recognition and Neural Network design and implementation |
| • Strong foundation in Computer Science with familiarity in algorithms, data structures, and computational models |
| • Experience in Software Development, including coding, testing, debugging, and process optimization |
| • Expertise in Natural Language Processing (NLP), including text analytics, language modeling, and contextual understanding |
| • Hands-on experience with machine learning frameworks and AI tools is a plus |
| • Comfortable working with distributed environments and large-scale data processing systems |
| • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field |
| • Excellent problem-solving skills, collaboration abilities, and a proactive mindset ",2026,Bachelors,0-1,"Python, ML, NLP","Communication, Problem Solving"
|
| 75,AI Engineer,Junior,"• 3–6 years of experience in Data Science, Machine Learning, or AI Engineering. |
| • Strong proficiency in Python for machine learning and data processing. |
| • Hands-on experience in machine learning model development and deployment. |
| • Experience working with Apache Kafka and streaming data processing. |
| • Strong understanding of feature engineering, model evaluation, and production ML workflows. |
| • Experience with AWS services including: |
| • AWS Lambda |
| • EventBridge |
| • SageMaker |
| • S3 |
| • Firehose |
| • CloudWatch |
| • Experience working with Snowflake and Snowpark. |
| • Knowledge of SQL and large-scale data processing. |
| • Experience building CI/CD pipelines and deployment automation. |
| • Hands-on experience with Terraform and cloud infrastructure management. |
| • Strong problem-solving and analytical skills ",2026,Bachelors,1-5,"Python, ML, LLMS, APIs, AWS/Azure, SQL, CI/CD, TensorFlow/Pytorch, Scikit-Learn","Communication, Problem Solving"
|
| 76,AI Engineer,Junior,"Hands-on experience with |
| LLMs and Agentic AI frameworks |
| Strong proficiency in |
| Python |
| and AI application development |
| Experience with |
| LangChain, LangGraph, AutoGen, CrewAI, OpenAI APIs, MCP |
| Knowledge of |
| RAG, vector databases, prompt engineering, tool usage, memory architectures |
| Exposure to |
| CI/CD, DevOps, DevSecOps workflows |
| Experience integrating AI into |
| developer platforms and enterprise workflows |
| Understanding of |
| security, governance, and scalable AI deployment |
| Preferred: |
| Experience with |
| GitHub Copilot, Claude, Codex |
| Exposure to |
| cloud platforms (AWS / Azure / GCP) |
| Experience building |
| developer productivity platforms ",2026,Bachelors,0-1,"Python, LLMs, ML, Agents, LangChain, LangGraph, AutoGen, CrewAI, OpenAI, APIs, MCP, RAG, VectorDB, CI/CD, Git, Github, AWS/Azure","Communication, Problem Solving"
|
| 77,AI Engineer,Junior,"• Bachelor’s or Master’s in Computer Science, AI, Data Science, or related field |
| Experience |
| • 2–5 years of hands-on experience in AI/ML or applied AI engineering |
| • Experience building end-to-end AI systems (not just experimentation) |
| • Exposure to LLMs and AI agents in production environments |
| Technical Skills (Must-Have) |
| • Strong Python programming skills |
| • Experience with LLMs (OpenAI, open-source models, etc.) |
| • Understanding of agent-based systems and tool integration |
| • Experience with APIs, microservices, and system integration |
| • Familiarity with cloud platforms (preferably GCP) |
| • Knowledge of software engineering best practices (testing, version control) |
| Preferred Skills (Good to Have) |
| • Experience with agent frameworks (LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel) |
| • Knowledge of RAG architectures and vector databases (Pinecone, ChromaDB, etc.) |
| • Familiarity with MLOps tools (Docker, CI/CD, model serving frameworks) |
| • Experience with structured outputs and function calling |
| • Exposure to CAE/FEA tools (ANSYS, Abaqus, LS-DYNA) |
| Core Competencies |
| • Agentic system design (planning, memory, orchestration) |
| • Prompt engineering and LLM optimisation |
| • Reliability engineering and AI safety practices |
| • Strong analytical thinking and problem-solving |
| • Effective cross-functional communication ",2026,Bachelors/Masters,1-5,"Python, ML, LLMs, AWS/Azure, APIs, Git, Github, LangChain, LangGraph, AutoGen, CrewAI, RAG, Docker, CI/CD, System Design, Prompt Engineering","Communication, Problem Solving, Analytical Skills"
|
| 84,AI Engineer,Junior,"• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field; or High School Diploma/General Education Degree and 4+ years of relevant as outlined in the essential duties in lieu of Bachelor’s Degree. |
| • Professional experience in AI/ML model development. |
| • Demonstrated ability working with machine learning frameworks, programming languages like Python, and cloud platforms. |
| • Demonstrated ability to learn new technologies. |
| • Demonstrated understanding of ethical considerations in AI systems. |
| • Strong analytical and problem-solving skills with understanding of AI/ML techniques. |
| Preferred Qualifications: |
| • Experience deploying Gen AI solutions at scale. |
| • Experience fine tuning LLMs, SLMs, teacher-student frameworks and model distillation. |
| • Familiarity with human in the loop methods for aligning LLMs with human preferences. |
| • Familiarity with agentic framework platforms and concepts. Experience deploying agentic-based solutions is a plus. ",2026,Bachelors,0-1,"Python, ML, TensorFlow/PyTorch, GenAI, LLMs, ","Communication, Problem Solving"
|
| 89,AI Engineer,Junior,"M.Tech (CS/IT) - Mandatory- Freshers (0 yrs) OR 1-2 years of experience in AI/ML- Strong interest in AI, machine learning, and automationKey Responsibilities : Build AI Solutions : - Develop AI/ML models and GenAI applications using LLMs- Build RAG pipelines, NLP models, and automation workflows- Work on real-world use cases across insurance & operationsCoding & Development (Core Focus) : - Write clean, scalable code using Python and ML frameworks- Work with HuggingFace, PyTorch, LangChain, APIs, and SQL- Design and implement end-to-end AI workflowsExperiment & Learn : - Work on prompt engineering, fine-tuning, and model optimisation- Explore techniques like LoRA / QLoRA, embeddings, vector DBs- Continuously experiment with new AI approaches and toolsDeployment & Integration : - Assist in deploying models using basic MLOps practices- Integrate AI solutions with internal systems via APIs and data pipelinesDrive Business Impact : - Understand business problems and convert them into AI use cases- Deliver measurable impact like: Process automation, TAT reduction, Efficiency improvement ",2026,Masters,1-5,"Python, ML, MLOps, Git, Github, LLMs, NLP, RAG, Agents, HuggingFace, TensorFlow/PyTorch, LangChain, APIs, SQL, VectorDB","Communication, Problem Solving"
|
| 94,AI Engineer,Junior,"• Strong foundation in Computer Science and Software Development, including data structures, algorithms, and version control. |
| • Experience with Pattern Recognition and Neural Networks for real-world applications such as classification, prediction, and recommendation systems. |
| • Hands-on expertise in Natural Language Processing (NLP), including text analysis, conversational interfaces, and language models. |
| • Proficiency with programming languages commonly used in AI (such as Python or JavaScript) and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). |
| • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience. |
| • Ability to work collaboratively on-site, communicate complex technical concepts clearly, and translate business needs into AI solutions. |
| • Experience deploying AI models into production environments and optimizing for scalability and performance is a plus. |
| • Familiarity with cloud platforms, APIs, and MLOps practices for model monitoring and continuous improvement is beneficial. ",2026,Bachelors/Masters,0-1,"Python, NLP, TensorFlow/PyTorch, Scikit-Learn, APIs, MLOps","Communication, Problem Solving"
|
| 101,AI Engineer,Junior,"• Assist in collecting, cleaning, and preprocessing datasets for ML models |
| • Build, train, and evaluate machine learning and deep learning models |
| • Support development and integration of AI features into existing products |
| • Work with frameworks like TensorFlow, PyTorch, or Scikit-learn |
| • Conduct exploratory data analysis (EDA) and document findings |
| • Help fine-tune and experiment with LLMs/NLP models (if applicable) |
| • Write clean, efficient, and well-documented Python code |
| • Collaborate with senior data scientists/engineers to understand business requirements |
| • Stay updated with the latest AI/ML research, tools, and best practices |
| Required Skills |
| • Strong foundation in Python programming |
| • Good understanding of Machine Learning concepts (supervised/unsupervised learning, regression, classification, clustering) |
| • Familiarity with libraries such as NumPy, Pandas, Scikit-learn |
| • Basic knowledge of Deep Learning (Neural Networks, CNNs, RNNs) is a plus |
| • Understanding of statistics and probability |
| • Familiarity with SQL and data handling |
| • Basic knowledge of Git/GitHub for version control ",2026,Not Specified,0-1,"Python, ML, TensorFlow/PyTorch, Scikit-Learn, LLMs, NLP, NumPy, Pandas, SQL, Git, Github","Communication, Problem Solving"
|
| 107,AI Engineer,Junior,"Strong understanding of AI/ML fundamentals, model development, and deployment strategies.
|
| Hands-on experience training and fine-tuning models (e.g., regression, classification, ranking, NLP).
|
| Familiarity with AdTech systems such as SSP, DSP, DMP, and RTB (Real-Time Bidding).
|
| Experience with AWS AI/ML services (SageMaker, Comprehend, Bedrock, etc.) or other cloud ML platforms.
|
| Proficiency in Python, TensorFlow, PyTorch, or similar frameworks.
|
| Ability to analyze business and campaign data and convert them into scalable AI solutions.
|
| Strong problem-solving skills, analytical mindset, and attention to detail.
|
| Good to Have (Optional):
|
| AWS Machine Learning Specialty or AI Practitioner certifications.
|
| Experience with RAG systems, LLMs, or Generative AI for AdTech use cases.
|
| Knowledge of MLOps and CI/CD pipelines for model deployment.
|
| Exposure automated campaign optimization, bid strategy modeling, or user segmentation algorithms
",2026,Not Specified,0-1,"Python, ML, NLP, AWS/Azure, TensorFlow/PyTorch, Scikit-Learn, RAG, LLMs, GenAI, MLOps, CI/CD","Communication, Problem Solving"
|
| 108,AI Engineer,Junior,"Strong foundation in Computer Science and Software Development, including data structures, algorithms, and version control.Experience with Pattern Recognition and Neural Networks for real-world applications such as classification, prediction, and recommendation systems.Hands-on expertise in Natural Language Processing (NLP), including text analysis, conversational interfaces, and language models.Proficiency with programming languages commonly used in AI (such as Python or JavaScript) and relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.Ability to work collaboratively on-site, communicate complex technical concepts clearly, and translate business needs into AI solutions.Experience deploying AI models into production environments and optimizing for scalability and performance is a plus.Familiarity with cloud platforms, APIs, and MLOps practices for model monitoring and continuous improvement is beneficial. ",2026,Bachelors/Masters,0-1,"Python, ML, NLP, Javascript, TensorFlow/PyTorch, Scikit-Learn, APUIs, MLOps, CI/CD","Communication, Problem Solving"
|
| 109,AI Engineer,Junior,"• Bachelor’s Degree in IT or equivalent Computer Science, Machine Learning, or related field. |
| • 5-8 years of professional experience in software development; you will be able to discuss in depth both the design and your significant contributions to one or more projects. |
| • Experience with open-source large language models and fine-tuning at scale |
| • Familiarity with vector databases, embedding models, and semantic search techniques |
| • Background in natural language processing (NLP) and understanding of transformer architecture internals |
| • Experience with model deployment, monitoring, and A/B testing in production environments |
| • Knowledge of responsible AI practices, including bias detection, fairness evaluation, and explainability |
| • Advanced expertise in enterprise automation frameworks and RPA (Robotic Process Automation) integration |
| • Experience with intelligent document understanding (IDP) platforms and layout analysis models |
| • Deep expertise in Oracle Cloud ecosystem, including OIC, VBCS, and APEX. |
| • Experience developing custom adapters and AI-connectors for OIC to integrate third-party systems |
| • Advanced PL/SQL performance tuning and database optimization on Oracle Database |
| • Certification in Oracle Cloud technologies (Oracle AI related, Integration Cloud, Oracle PAAS) |
| • Custom Role Development and Cloud System Administration services |
| • Good knowledge in any of (Order to Cash) or (Procure to Pay) custom development experience in automated AR/AP Invoices or Bank Statement integration |
| • Hands-on knowledge of Security roles in Fusion, page personalization, and Web Services is a definite plus. |
| • Determination, self-motivation, and an eagerness to take on new challenges. |
| • Ability to adapt quickly, working in a dynamic business environment. |
| • Excellent analytical and problem-solving skills. ",2026,Bachelors,0-1,"Python, ML, NLP, SQL","Communication, Problem Solving"
|
| 110,AI Engineer,Junior,"• Strong programming skills in Python. |
| • Experience with machine learning frameworks such as: |
| o TensorFlow |
| o PyTorch |
| o Scikit-learn |
| • Knowledge of deep learning architectures (CNN, RNN, Transformers). |
| • Experience with data processing tools such as Pandas, NumPy, and Spark. |
| • Familiarity with model deployment using Docker, FastAPI, or Flask. |
| • Understanding of MLOps practices. |
| • Experience with cloud platforms such as AWS, GCP, or Azure. |
| • Knowledge of Git and CI/CD pipelines. |
| Preferred Qualifications: |
| • Experience with LLMs and Generative AI. |
| • Knowledge of vector databases and embeddings. |
| • Familiarity with LangChain or LLM orchestration frameworks. |
| • Experience building AI-powered APIs or chatbots. |
| • Exposure to Kubernetes and scalable ML infrastructure. |
| Education |
| • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field. ",2026,Bachelors/Masters,0-1,"Python. ML, LLMs, TensorFlow/PyTorch, Scikit-Learn, Pandas, NumPy, APIs, Docker, MLOps, Git, Github, CI/CD, AWS/Azure, GenAI, LangChain, LangGraph, LlamaIndex, Agents, GenAI, Kubernetes, ","Communication, Problem Solving"
|
| 112,AI Engineer,Junior,"• Bachelor's degree in Computer Science, Data Science, AI/ML, or a related field (or final-year student/intern). |
| • Strong foundation in Java and Python and familiarity with ML libraries like scikit-learn, TensorFlow, or PyTorch. |
| • Basic understanding of LLMs and their applications (e. g., chatbots, text classification, summarization), openAI or claude. |
| • Exposure to data analysis tools like Pandas, NumPy, and SQL. |
| • Familiarity with Git and version control practices. |
| • Willingness to learn and contribute in a fast-paced, collaborative environment. |
| • Academic or personal projects involving ML/AI or NLP. |
| • Experience with cloud platforms (AWS, GCP, or Azure) or Docker. |
| • Exposure to tools like LangChain, Hugging Face Transformers, or vector databases. |
| • Participation in AI/ML competitions (e. g., Kaggle) or open-source contributions. ",2026,Bachelors,0-1,"Python, ML, Java, Pandas, NumPy, SQL, Git, Github, NLP, AWS/Azure, Docker, LangChain, LangGraph, Agents, OpenAI, LLMs, TensorFlow/Pytorch, Scikit-Learn","Communication, Problem Solving"
|
| 113,AI Developer,Junior,"1. 1-2 years of software engineering experience, ideally in a product-focused or startup environment. 2. Strong Python skills: You write clean, maintainable code and have experience with modern backend frameworks. 3. Database Fundamentals: Comfortable writing SQL and working with relational databases (especially PostgreSQL). You aren't afraid of complex queries or working with JSON/JSONB data types. 4. AI/ML Basics: Practical experience working with LLM APIs (OpenAI, Anthropic, etc.) and a foundational understanding of text embeddings, tokenization, and semantic search. ",2026,Bachelors,0-1,"Python, SQL, APIs, OpenAI, LLMs","Communication, Problem Solving"
|
| 114,AI Engineer,Junior,"- Minimum bachelors degree in computer science, Mathematics, Engineering, Statistics, or a related field. |
| - At least 1 year of experience in Natural Language Processing (NLP), Machine Learning, Generative AI specifically with Large Language Models (LLM). |
| - Proficiency in Python and other applicable full-stack software programming languages. |
| - Strong knowledge of machine learning, language modeling, data mining, and predictive modeling. |
| - Excellent understanding of data science algorithms, processes, tools, and platforms. |
| - Strong problem-solving mindset, with the ability to work in ambiguous and fast-paced environments. |
| - Knowledge of API integration, containerization (e.g., Docker), cloud platforms (e.g., Azure, AWS, GCP), automated testing frameworks, and CI/CD practices. ",2026,Bachelors,0-1,"Python, NLP, ML, APIs, Docker, AWS/Azure, CI/CD","Communication, Problem Solving"
|
| 115,AI Engineer,Junior,"• Bachelor's degree in Computer Science, Data Science, AI/ML, or a related field (or final-year student/intern). |
| • Strong foundation in Java and Python and familiarity with ML libraries like scikit-learn, TensorFlow, or PyTorch. |
| • Basic understanding of LLMs and their applications (e. g., chatbots, text classification, summarization), openAI or claude. |
| • Exposure to data analysis tools like Pandas, NumPy, and SQL. |
| • Familiarity with Git and version control practices. |
| • Willingness to learn and contribute in a fast-paced, collaborative environment. |
| • Academic or personal projects involving ML/AI or NLP. |
| • Experience with cloud platforms (AWS, GCP, or Azure) or Docker. |
| • Exposure to tools like LangChain, Hugging Face Transformers, or vector databases. |
| • Participation in AI/ML competitions (e. g., Kaggle) or open-source contributions ",2026,Bachelors,0-1,"Python, NLP, SQL, Git, Github, Pandas, NumPy, TensorFlow/PyTorch, Scikit-Learn, LLMs, OpenAI, AWS/Azure, Docker, LangChain, LangGraph, Hugging Face, VectorDB","Communication, Problem Solving"
|
| 117,AI Engineer,Junior,"Solid programming experience in Python / R / C / C++ .
|
| Robust understanding of:
|
| Machine Learning algorithms
|
| Deep Learning architectures
|
| Model evaluation techniques
|
| Data preprocessing
|
| Hands-on experience with:
|
| TensorFlow
|
| Keras
|
| PyTorch
|
| Experience working with Computer Vision, NLP, and Predictive Analytics projects.
|
| Solid problem-solving and analytical skills.
|
| Ability to convert business problems into AI/ML solutions.
|
| Experience deploying ML models into production environments.
|
| Knowledge of MLOps, APIs, cloud platforms, or model monitoring is a plus.
",2026,Bachelors,0-1,"Python, C, C++, R, ML, TensorFlow/PyTorch, NLP, MLOps, APIs, AWS/Azure","Communication, Problem Solving"
|
| 118,AI Engineer,Junior,"Strong understanding of
|
| AI agents
|
| and experience in building agents/skills
|
| Hands-on experience with
|
| LLM integration
|
| and advanced prompt engineering
|
| Expertise in
|
| time-series forecasting
|
| or predictive modeling (preferably in automotive/fleet domains)
|
| Proficiency in Python ML ecosystem:
|
| scikit-learn, pandas , and ideally
|
| PyTorch/TensorFlow
|
| Solid knowledge of
|
| RAG (Retrieval-Augmented Generation)
|
| frameworks
|
| Experience in
|
| model evaluation , experimentation, and A/B testing
",2026,Bachelors,0-1,"Python, Agents, LangChain, LangGraph, LlamaIndex, LLMs, ML, Pandas, Scikit-Learn, TensorFlow/PyTorch, RAG","Communication, Problem Solving"
|
| 119,AI Engineer,Junior,"• Strong production-level software engineering skills, with depth in either Python/backend systems or React/TypeScript/frontend systems, and willingness to work across both |
| • Ability to take clear product goals, make good technical decisions, and ship reliable software without heavy process |
| • Experience using AI coding tools such as Cursor, Claude Code, or similar tools in real development work |
| • Genuine interest in AI systems and hardware design |
| • Clear written and verbal communication |
| • Experience with LLM applications, agents, evals, LangChain, tool use, or prompt engineering |
| • Experience building desktop apps, Electron apps, complex frontend state, or developer tools |
| • Hardware project experience: robots, drones, embedded systems, PCBs, Formula Student, KiCad/Altium, firmware, or electronics prototyping |
| • ECE or CS background, or equivalent demonstrated experience across software and hardware |
| • Examples of shipped products, side projects, open-source work, research papers, or technical demos you can walk us through ",2026,Bachelors,0-1,"Python, React, LLMs, Agents, LangChain, LangGraph, LlamaIndex, Prompt Engineering","Communication, Problem Solving"
|
| 121,AI Engineer,Junior,"Generative AI & NLP Expertise: Extensive experience in developing and deploying Generative AI applications and NLP frameworks, with hands-on knowledge of LLM fine-tuning, model customization, and AI-powered automation. |
| Hands-On Data Science Experience: 4+ years of experience in data science, with a proven ability to build and operationalize machine learning and NLP models in real-world environments. |
| AI Innovation: Deep knowledge of the latest developments in Generative AI and NLP, with a passion for experimenting with cutting-edge research and incorporating it into practical solutions. |
| Problem-Solving Mindset: Strong analytical skills and a solution-oriented approach to applying data science techniques to complex business problems. |
| Communication Skills: Exceptional ability to translate technical AI concepts into business insights and recommendations for non-technical stakeholders.",2026,Bachelors,0-1,"Python, ML, NLP, GenAI, LLMs","Communication, Problem Solving"
|
| 123,AI Engineer,Junior,"• Minimum 1 year of hands-on experience building AI use cases
|
| • Proven experience creating multiple AI workflows
|
| • Experience building or working with AI agents and agentic workflows
|
| • Strong understanding of Large Language Models and their practical applications
|
| • Good knowledge of Retrieval-Augmented Generation
|
| • Strong proficiency in Python
|
| • Experience connecting AI models with APIs, databases, documents or business systems
|
| • Ability to take a requirement from idea to working solution
|
| • Understanding of prompt engineering, structured outputs and function or tool calling
|
| • Ability to independently take a business requirement and convert it into a working AI solution
|
| • Strong problem-solving and experimentation skills
|
| What Matters Most
|
| We are specifically looking for someone who can demonstrate:
|
| • Workflows they have personally built
|
| • AI agents they have worked with or developed
|
| • How they have used LLMs in practical applications
|
| • The business problem solved and the final outcome
",2026,Bachelors,0-1,"Python, ML, Agents, LLMs, RAG, LangChain, LangGraph, APIs, SQL, VectorDB","Communication, Problem Solving"
|
| 124,AI Developer,Junior,"• 1+ years of experience in Generative AI or LLM application development.
|
| • Hands-on experience with LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
|
| • Strong Python programming skills.
|
| • Good understanding of APIs, JSON, vector databases, and embeddings.
|
| • Familiarity with prompt engineering and RAG concepts.
|
| • Passion for building real-world AI products.
|
| Good to Have
|
| • Experience with LangSmith.
|
| • Knowledge of MCP, tool calling, and AI orchestration.
|
| • Experience with Azure AI, OpenAI, or Anthropic APIs.
|
| • Knowledge of Docker and cloud deployment.
|
| • Experience using Cursor, Codex, or Claude Code.
",2026,Bachelors,1-5,"Python, GenAI, LLMs, Agents, LangChain, LangGraph, CrewAI, AutoGen, APIs, VectorDB, RAG, MCP, OpenAI, Docker, AWS/Azure","Communication, Problem Solving"
|
| 125,AI Engineer,Junior,"• Strong experience with React.js, Next.js, Node.js, TypeScript, Python, FastAPI, REST APIs, SQL/NoSQL databases, and Git. |
| • Understanding of Machine Learning algorithms, model deployment, and software development best practices. |
| • Experience with OpenAI, Gemini, Claude, and similar AI/ML frameworks. |
| • Familiarity with LangChain, LangGraph, RAG, Vector Databases, Prompt Engineering, and AI Agents. |
| • Experience using GitHub Copilot, Cursor, Claude Code, or similar AI development tools. |
| Preferred Skills |
| • Experience with AWS/GCP/Azure, MLOps, and cloud deployment. |
| • Strong analytical thinking, debugging, and problem-solving skills. ",2026,Bachelors,0-1,"Python, SQL, Javascript, React, APIs, Git, Github, ML, Agents, OpenAI, LangChain, LangGraph, VectorDB, RAG, Prompt Engineering, AWS/Azure, MLOps","Communication, Problem Solving"
|
| 126,AI Engineer,Junior,"Strong experience with machine learning and natural language processing. |
| Experience working with large language models (LLMs), prompt engineering, retrieval-augmented systems, or conversational AI. |
| Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow. |
| Experience developing mobile or cross-platform applications. |
| Understanding of healthcare data privacy, security, and ethical AI principles. |
| Ability to work effectively in multidisciplinary clinical and technical teams. |
| Preferred Qualifications |
| Experience in digital health, health technology, medical devices, or assistive technologies. |
| Familiarity with speech-language pathology, aphasia, neuro-oncology, or neurological disorders. |
| Experience with user-centered design and accessibility-focused product development. |
| Knowledge of clinical research methodologies and healthcare regulations. |
| Experience deploying AI systems in real-world healthcare environments. ",2026,Bachelors,0-1,"Python, ML, Prompt Engineering, LLMs, RAG, GenAI, TensorFlow/PyTorch","Communication, Problem Solving"
|
| 128,AI Engineer,Junior,"• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field; or High School Diploma/General Education Degree and 4+ years of relevant as outlined in the essential duties in lieu of Bachelor’s Degree. |
| • Professional experience in AI/ML model development. |
| • Demonstrated ability working with machine learning frameworks, programming languages like Python, and cloud platforms. |
| • Demonstrated ability to learn new technologies. |
| • Demonstrated understanding of ethical considerations in AI systems. |
| • Strong analytical and problem-solving skills with understanding of AI/ML techniques. |
| Preferred Qualifications: |
| • Experience deploying Gen AI solutions at scale. |
| • Experience fine tuning LLMs, SLMs, teacher-student frameworks and model distillation. |
| • Familiarity with human in the loop methods for aligning LLMs with human preferences. |
| • Familiarity with agentic framework platforms and concepts. Experience deploying agentic-based solutions is a plus. ",2026,Bachelors,0-1,"Python, ML, GenAI, LLMs","Communication, Problem Solving"
|
| 129,AI Developer,Junior,"Node.js / Express · Claude API (Anthropic) · Supabase · Wati (WhatsApp Business API) · node-cron · Jest · DigitalOcean VPS
|
| You're right for this if you:
|
| • Have shipped production Node.js APIs that real users hit
|
| • Are comfortable with webhooks, async JavaScript, and third-party API integrations
|
| • Have worked with PostgreSQL or Supabase
|
| • Can deploy a backend to a VPS without hand-holding
|
| • Write tests and don't consider them optional
|
| • (Bonus if you've built with Claude / OpenAI or WhatsApp Business API before)
",2026,Bachelors,0-1,"Python, Javascript, APIs, SQL, OpenAI, GenAI","Communication, Problem Solving"
|
| 130,AI Engineer,Junior,"• 0–4 years of experience in Machine Learning, NLP, Speech AI, or Applied AI. |
| • Strong proficiency in Python. |
| • Experience with PyTorch, TensorFlow, or similar ML frameworks. |
| • Knowledge of NLP frameworks such as Hugging Face, spaCy, or NLTK. |
| • Understanding of model training, evaluation, and deployment. |
| • Strong analytical and problem-solving skills. |
| Good to Have |
| • Experience with Whisper, Wav2Vec2, Kaldi, DeepSpeech, or similar speech technologies. |
| • Experience with LLMs and Generative AI applications. |
| • Familiarity with FastAPI, Docker, and cloud platforms (AWS/GCP/Azure). |
| • Exposure to MLOps and production ML systems. |
| • Understanding of language assessment, educational testing, or communication evaluation platforms. ",2026,Bachelors,0-1,"Python, ML, NLP, TensorFlow/PyTorch, Huging Face, LLMs, GenAI, APIs, Docker, AWS/Azure, MLOps","Communication, Problem Solving"
|
| 131,AI Engineer,Junior,"Strong understanding of Python
|
| Basic knowledge of Machine Learning concepts
|
| Familiarity with libraries like NumPy, Pandas, Scikit-learn
|
| Understanding of data preprocessing and model evaluation
|
| Basic knowledge of NLP, Computer Vision, or Generative AI
|
| Ability to work with APIs and AI tools
|
| Positive analytical and problem-solving skills
|
| Valuable to Have
|
| Knowledge of TensorFlow or PyTorch
|
| Experience with OpenAI APIs or other LLM tools
|
| Basic understanding of SQL and databases
|
| Experience with college projects, internships, or GitHub projects
|
| Knowledge of automation tools and AI agents
|
| Eligibility Criteria
|
| Bachelor’s degree in:
|
| Computer Science
|
| BCA / MCA
|
| B.Tech / M.Tech
|
| Artificial Intelligence
|
| Data Science
|
| Mathematics
|
| Statistics
|
| Or related fields
",2026,Bachelors/Masters,0-1,"Python, ML, NumPy, Pandas, Scikit-Learn, NLP, GenAI, APIs, TensorFlow/PyTorch, OpenAI, LLMs, SQL","Communication, Problem Solving"
|
| 133,AI Engineer,Junior,"• Python
|
| • LangChain
|
| • OpenAI / Anthropic APIs
|
| • Prompt Engineering
|
| • Vector Databases (Basic)
|
| • FastAPI
|
| • Git
|
| • PostgreSQL
",2026,Bachelors,0-1,"Python, LangChain, LangGraph, Agents, OpenAI, Prompt Engineering, VectorDB, APIs, Git, Github, SQL","Communication, Problem Solving"
|
| 135,AI Engineer,Junior,"• * Education: Bachelors degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience). |
| • * Familiarity with AI/ML Concepts: Basic understanding of artificial intelligence, machine learning, and data science. |
| • * Attention to Detail: Strong focus on data accuracy, precision, and consistency. |
| • * Technical Skills: Proficiency with spreadsheets (Excel/Google Sheets) and data processing tools. |
| • * Communication Skills: Strong written and verbal communication skills to document processes and work with cross-functional teams. |
| • * Problem-Solving Abilities: Ability to identify challenges in data and propose efficient solutions. |
| • * Tech-Savvy: Willingness to learn and adapt to new tools and technologies relevant to AI/ML projects. |
| • Experience: |
| • * Entry-level position ideal for recent graduates or individuals with a passion for AI/ML. |
| • * Previous experience in data annotation, data entry, or any technical support role is a plus but not mandatory. |
| • Working Hours: |
| • * Full-time (40 hours per week). |
| • * Flexible working hours to accommodate global team collaboration. |
| • * Remote work opportunity with potential for occasional team meetings via video calls. |
| • Knowledge, Skills, and Abilities: |
| • * Knowledge of Data Preparation: Basic understanding of data cleaning, normalization, and preprocessing for machine learning models. |
| • * Analytical Skills: Ability to analyze and manipulate datasets to extract meaningful insights. |
| • * Familiarity with AI Tools: Exposure to basic AI tools and platforms such as TensorFlow, PyTorch, or similar technologies is beneficial. |
| • * Adaptability: Willingness to learn and grow within the dynamic field of AI/ML. |
| • * Team Collaboration: Ability to work effectively in a remote, collaborative environment. |
| • Benefits: |
| • * Competitive Salary: Competitive pay based on experience and skill level. |
| • * Learning and Development: Access to training resources, mentorship, and opportunities to grow within the AI/ML field. |
| • * Remote Work Flexibility: Work from the comfort of your home with flexible hours. |
| • * Health and Wellness Benefits: Comprehensive health insurance and wellness programs. |
| • * Career Growth: Opportunity for advancement in a rapidly growing industry. |
| • * Team Collaboration: Work alongside highly skilled professionals in a supportive, remote work environment. ",2026,Bachelors,0-1,"Python, ML, TensorFlow/PyTorch, GenAI, LLMs","Communication, Problem Solving"
|
| 142,AI Developer,Junior,"Job DescriptionAre you passionate about Python and curious about AI/ML?Join us to kickstart your career with hands-on experience in real-world machine learning projects!What Youll Work OnPython coding for AI/ML applicationsData preprocessing, model training & deploymentCollaborate with engineers and analysts on end-to-end AI solutionsExplore data and visualize insights using popular Python librariesPreferred SkillsStrong Python fundamentalsBasic ML concepts & libraries (NumPy, Pandas, Scikit-learn)Aptitude for problem-solving & statisticsFamiliarity with tools like Git, Matplotlib, or Seaborn is a plusConsistent academic performance with 70% or equivalent and above throughoutRequirementsAre you passionate about Python and curious about AI/ML? Join us to kickstart your career with hands-on experience in real-world machine learning projects! What youll work on: Python coding for AI/ML applications Data preprocessing, model training & deployment Collaborate with engineers and analysts on end-to-end AI solutions Explore data and visualize insights using popular Python libraries Preferred Skills Strong Python fundamentals Basic ML concepts & libraries (NumPy, Pandas, Scikit-learn) Aptitude for problem-solving & statistics Familiarity with tools like Git, Matplotlib, or Seaborn is a plus Consistent academic performance with 70% or equivalent and above throughout ",2026,Bachelors,0-1,"Python, ML, NumPy, Pandas, Scikit-Learn, APIs, Git, Github","Communication, Problem Solving"
|
| 143,AI Developer,Junior,"• Strong programming skills in Python (FastAPI, Flask) or Node.js. |
| • Exposure to NLP, LLMs, AI APIs (ChatGPT, Perplexity.ai, LangChain). |
| • Familiarity with RESTful APIs and Graph Databases (Neo4j). |
| • Basic understanding of cloud platforms (AWS, Azure, GCP). |
| • Passion for AI, NLP, and chatbot development. |
| • Bonus: Knowledge of UI frameworks (React, Next.js). |
| • Good to have - Pinecone or equivalent vector databases. ",2026,Bachelors,0-1,"Python, ML, APIs, LLMs, NLP, AWS/Azure, VectorDB","Communication, Problem Solving"
|
| 144,AI Developer,Junior,"The ideal candidate will be responsible for developing and debugging responsive web applications for the company. Using Python, Django, JavaScript, this candidate will be able to translate user and business needs into functional products. Must have knowledge in PythonDjangoExperience in Gen-AI APIs, RAGDatabase schema modeling and designingBasics in CSS, Bootstrap, Bulma etcTools like web-pack, npm, yarn etc.Good sense of designVersion controlling and GitHub ",2026,Bachelors,0-1,"Python, APIs, Django, Javascript, GenAI, RAG, SQL, Git, Github","Comunication, Problem Solving"
|
| 172,AI Developer,Junior,"We are looking for a passionate Junior AI Automation Engineer to build AI-powered automation systems using open-source technologies. You will work on AI agents, browser automation, backend APIs, and workflow automation—not UI/UX development. Strong knowledge of Python, FastAPI, GitHub, Railway, Vercel, Playwright, REST APIs, and PostgreSQL is required. Experience with LLMs (OpenAI/Claude/Gemini), LangChain/LangGraph, n8n, Docker, MCP, or RAG is a plus. You should be comfortable integrating APIs, deploying applications, and solving real-world business problems through automation. We value hands-on builders with working GitHub projects over certifications. Fresh ideas, curiosity, and a willingness to learn are essential. ",2026,Bachelors,0-1,"Python, ML, SQL, APIs, LLMs, n8n, Agents, LangChain, LangGraph, Docker, MCP, RAG, Github, Git","Communication, Problem Solving"
|
| 173,AI Developer,Junior,"• * 1–2 years of hands-on experience in Python AI/ML development. |
| • Strong understanding of core Python concepts, data structures, and algorithms. |
| • Experience with frameworks such as Django, Flask, or FastAPI. |
| • Familiarity with RESTful APIs and microservices architecture. |
| • Good understanding of databases (MySQL, PostgreSQL, or NoSQL). |
| • Experience with version control systems like Git. |
| • Strong debugging and problem-solving skills. |
| • Strong communication and collaboration skills. |
| • Exposure to AI/ML concepts or AI-assisted development (e.g., prompt engineering, AI coding tools). |
| • Experience working on international/global projects. |
| • Familiarity with cloud platforms (AWS, Azure, or GCP). |
| • Knowledge of containerization tools like Docker. |
| • Understanding of CI/CD pipelines and DevOps practices. ",2026,Bachelors,0-1,"Python, ML, APIs, Django, SQL, Git, Github, AWS/Azure, Docker, CI/CD, Prompt Engineering","Communication, Problem Solving"
|
| 174,AI Developer,Junior,"Required Qualifications |
| Strong experience with machine learning and natural language processing. |
| Experience working with large language models (LLMs), prompt engineering, retrieval-augmented systems, or conversational AI. |
| Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow. |
| Experience developing mobile or cross-platform applications. |
| Understanding of healthcare data privacy, security, and ethical AI principles. |
| Ability to work effectively in multidisciplinary clinical and technical teams. |
| Preferred Qualifications |
| Experience in digital health, health technology, medical devices, or assistive technologies. |
| Familiarity with speech-language pathology, aphasia, neuro-oncology, or neurological disorders. |
| Experience with user-centered design and accessibility-focused product development. |
| Knowledge of clinical research methodologies and healthcare regulations. |
| Experience deploying AI systems in real-world healthcare environments. ",2026,Bachelors,0-1,"Python, GenAI, LLMs, Agents, LangChain, OpenAI, RAG, VectorDB, NLP, Prompt Engineering, TensorFlow/PyTorch, ","Communication, Problem Solving"
|
| 175,AI Developer,Junior,"Required Skills & Qualifications: |
| • Strong logical and analytical thinking. |
| • Good communication and collaboration skills. |
| • Quick learner with a strong willingness to upskill. |
| • Strong Python programming skills (loops, OOP, libraries). |
| • Basic understanding of Artificial Intelligence and Machine Learning concepts. |
| • Familiarity with libraries such as NumPy, Pandas, Matplotlib, scikit-learn, or TensorFlow/PyTorch (basic level). |
| • Understanding of APIs and how to integrate them. |
| • Knowledge of chatbot development tools or frameworks is a plus (e.g., Rasa, LangChain, OpenAI API). |
| • Strong problem-solving and analytical skills. |
| • Eagerness to learn new AI technologies and tools. |
| Preferred (But Not Mandatory): |
| • Knowledge of chatbot frameworks (e.g., Rasa, LangChain, Dialogflow). |
| • Experience with AI data visualization tools or dashboard development. |
| • Awareness of Natural Language Processing (NLP) concepts. ",2026,Bachelors,0-1,"Python, ML, Pandas, NumPy, Scikit-Learn, TensorFlow/PyTorch, APIs, Agents, LangChain, NLP, OpenAI","Communication, Problem Solving"
|
| 176,AI Developer,Junior,"Design, train, and fine-tune AI/ML models using Python frameworks. Work on LLMs, prompt engineering, data preprocessing, and model evaluation. Develop AI-based applications integrating NLP, computer vision, or generative content systems. |
| Required Candidate profile |
| Strong understanding of Python, ML, and deep learning concepts. Familiar with Generative AI tools (OpenAI, Hugging Face, LangChain, etc.). Eager to explore LLMs and prompt-based systems. ",2026,Bachelors,0-1,"Python, LLMs, NLP, Prompt Engineering, ML, GenAI, OpenAI, Hugging Face, LangChain","Communication, Problem Solving"
|
| 183,AI Developer,Junior,"1-2 years of software engineering experience, ideally in a product-focused or startup environment. 2. Strong Python skills: You write clean, maintainable code and have experience with modern backend frameworks. 3. Database Fundamentals: Comfortable writing SQL and working with relational databases (especially PostgreSQL). You aren't afraid of complex queries or working with JSON/JSONB data types. 4. AI/ML Basics: Practical experience working with LLM APIs (OpenAI, Anthropic, etc.) and a foundational understanding of text embeddings, tokenization, and semantic search. ",2026,Bachelors,0-1,"Python, ML, SQL. LLMs, APIs, OpenAI","Communication, Problem Solving"
|
| 184,AI Developer,Junior,"Requirements: Backend development experience with Python, including exposure to building or consuming APIs. |
| Foundational knowledge of LLMs, AI agents, RAG systems, or ML-driven applications, including hands-on project or coursework experience. |
| Familiarity with cloud platforms, preferably Azure. |
| Basic understanding of data security, governance, and reliability principles. |
| Ability to write clean, maintainable code and collaborate within a team environment. |
| Good communication skills and a willingness to learn in a fast-moving technical domain. |
| Nice to have: Exposure to financial services, enterprise data, or data-heavy domains is a plus. |
| Interest in semantic data modeling or knowledge graphs. Any experience with workflow automation tools or rules engines. |
| Awareness of enterprise AI governance and compliance considerations.",2026,Bachelors,0-1,"Python, ML, LLMs, RAG, Agents, LangChain, LangGraph, AWS/Azure, n8n","Communication, Problem Solving"
|
| 191,AI Developer,Junior,"Education: |
| Bachelor s degree in Engineering, Computer Science, Data Science, Gen AI or related fields. Final-year students or recent graduates are welcome to apply. |
| Technical Skills: |
| Strong foundation in Java, React, NodeJS, Python, SQL, and Excel |
| Basic understanding of data structures, databases, and algorithms |
| Exposure to pandas, NumPy, PySpark, scikit-learn, GenAI, Agentic AI or TensorFlow is a plus |
| Familiarity with BI tools (e.g., Power BI, Tableau) or cloud platforms (e.g., AWS, GCP) is desirable |
| Knowledge of version control (Git) is an advantage |
| Soft Skills |
|
|
| Curiosity and a passion for data-driven problem solving |
| Strong analytical and logical thinking |
| Good communication and collaboration skills |
| Willingness to learn in a fast-paced environment |
| Ability to break down complex problems and document clearly |
| Preferred (Good to Have, Not Mandatory) |
|
|
| Internship or academic project in data analytics, machine learning, or database systems |
| Participation in hackathons, coding contests, or Kaggle competitions |
| Exposure to Agile or collaborative tools like JIRA, Confluence",2026,Bachelors,0-1,"Python, Java, React, SQL, NumPy,Scikit-Learn, Javascript, GenAI, Agents, LangChain, LangGraph, Github, Github TensorFlow/PyTorch, AWS/Azure","Communication, Problem Solving"
|
| 192,AI Developer,Junior,"Work on AI applications involving NLP, Computer Vision, and Predictive Analytics. |
| Collaborate with senior developers to implement AI-driven solutions. |
| Perform data analysis and generate actionable insights. |
| Test, debug, and optimize AI/ML models for performance and accuracy. |
| Stay updated with the latest advancements in AI, Machine Learning, and Generative AI. |
| Required Skills Basic knowledge of Python programming. |
| Understanding of Machine Learning algorithms and concepts. |
| Familiarity with libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy. |
| Basic understanding of Data Structures and Algorithms. |
| Knowledge of SQL and database concepts. |
| Strong analytical and problem-solving skills. |
| Good communication and teamwork abilities. ",2026,Bachelors,0-1,"Python, ML, NLP, GenAI, SQL, TensorFlow/PyTorch, Scikit-Learn, NumPy, Pandas, ","Communication, Problem Solving"
|
| 193,AI Developer,Junior,"Strong programming skills in Python (FastAPI, Flask) or Node.js.
|
| Exposure to NLP, LLMs, AI APIs (ChatGPT, Perplexity.ai, LangChain).
|
| Familiarity with RESTful APIs and Graph Databases (Neo4j).
|
| Basic understanding of cloud platforms (AWS, Azure, GCP).
|
| Passion for AI, NLP, and chatbot development.
|
| Bonus: Knowledge of UI frameworks (React, Next.js).
|
| Good to have - Pinecone or equivalent vector databases.
",2026,Bachelors,0-1,"Python, APIs, Javascript, NLP, LLMs, LangCgain, LangGraph, AWS/Azure, React, VectorDB","Communication, Problem Solving"
|
| 198,AI Developer,Junior,"Design, develop, and implement state-of-the-art generative AI models, including Large Language Models (LLMs), Diffusion Models, GANs, and VAEs, for various applications. |
| Research and evaluate new generative AI techniques and frameworks to identify opportunities for innovation and improvement. |
| Optimize and fine-tune existing generative models for performance, efficiency, and scalability. |
| Integrate generative AI solutions into existing product pipelines and develop new APIs for seamless interaction. |
| Collaborate with data scientists, machine learning engineers, and product managers to define requirements, design solutions, and deliver high-quality AI-powered features. |
| Develop robust MLOps practices for deploying, monitoring, and maintaining generative AI models in production environments. |
| Conduct rigorous testing, validation, and evaluation of models to ensure accuracy, reliability, and ethical compliance. |
| Stay abreast of the latest research and developments in generative AI and machine learning, applying relevant insights to ongoing projects. |
| Document technical designs, model architectures, and implementation details clearly and comprehensively. |
| Participate in code reviews, contributing to a culture of high-quality code and best practices.",2026,Bachelors,0-1,"Python, LLMs, GenAI, MLOps, APIs","Communication, Problem Solving"
|
| 199,AI Developer,Junior,"0 to 1 years of professional experience in AI Agent Developer. |
| Proficient in Python and deep learning frameworks like PyTorch and TensorFlow. |
| Strong skills in time-series data analysis, feature engineering, and model optimization. |
| Familiarity with reinforcement learning algorithms and methodologies. |
| Experience with cloud platforms (GCP, AWS, Azure), container technologies (Docker, Kubernetes), and microservices. |
| A proven record of deploying ML models and developing autonomous AI agents. |
| Knowledge of AI-driven process optimization tools including AI orchestration for enterprise workflows. |
| Experience in troubleshooting ML systems |
| Adept at proactive problem identification and resolution. |
| Certification in MLOps is a plus.",2026,Bachelors,0-1,"Python, Agents, LangChain, LangGraph, TensorFlow/PyTorch, AWS/Azure, ML, MLOps","Communication, Problem Solving"
|
| 190,AI Developer,Junior,"Solid DS & Algo, analytical mindset
|
| Strong in Python (FastAPI/Flask/Django) or Node.js
|
| Good knowledge of ReactJS and UI
|
| Experience with REST APIs and ChatGPT integration
|
| Strong in database design and queries
",2026,Bachelors/Masters,0-1,"Python, APIs, Django, Javascript, GenAI, SQL","Communication, Problem Solving"
|
| 191,AI Developer,Junior,"Strong analytical and problem-solving skills
|
| Basic understanding of AI/ML concepts
|
| Familiarity with Python or JavaScript
|
| Understanding of APIs and backend systems
|
| Preferred Qualifications
|
| Background in Computer Science, Engineering, or Mathematics
|
| Exposure to AI tools (LangChain, OpenAI APIs)
|
| Participation in projects, hackathons, or internships
",2026,Bachelors,0-1,"Python, ML, Javascript, APIs, Agents, OpenAI, LangChain, LangGraph","Communication, Problem Solving"
|
| 193,AI Developer,Junior,"Bachelor s degree in Computer Science, IT, or related field |
| 0 3 years of experience (Freshers with strong fundamentals can apply) |
| Strong understanding of software testing concepts (SDLC, STLC, defect lifecycle) |
| Good analytical and problem-solving skills |
| Ability to understand business logic and workflows quickly |
| Strong verbal and written communication skills |
| Basic understanding of: |
| Manual testing techniques |
| API testing concepts |
| Databases (SQL basics) |
| Familiarity with tools like JIRA or similar bug tracking tools |
| Good to Have (Not Mandatory) |
| Exposure to automation tools (Selenium or similar) |
| Basic programming knowledge ( Java / JavaScript / HTML / CSS ) |
| Experience or understanding of Agile/Scrum |
| Awareness of Git/GitHub |
| Understanding of non-functional testing (performance, security basic level)",2026,Bachelors,0-1,"Python, APIs, SQL, Java, Javascript, Git, Github","Communication, Problem Solving"
|
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