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| Title,Company,Job Link,Apply Link,Description,img_link | |
| AI/ML Intern,Hyperqube Ionic,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| As an AI/ML intern, you will have the opportunity to work on cutting-edge projects at the intersection of artificial intelligence, machine learning and private market investments. We view this internship as a 3–6 month interview for your permanent seat at the table. | |
| You will be using your knowledge of and experience in Python, artificial intelligence, natural language processing (NLP), neural networks, machine learning, LLMs and modern, scalable AI technologies to develop innovative, technology-driven solutions for our company. | |
| Company Overview: | |
| Hyperqube Ionic is at the forefront of developing scalable technology infrastructure redefining how private capital forms conviction, builds trust, and moves into companies. Through our proprietary technology and machine learning algorithms, we uncover hidden signals, standardize information, unlock better decision-making, cull noise, and ensure faster outcomes. | |
| We are pioneering the development of the missing operating system of private markets with the objective of eliminating the outdated practices that make private markets inefficient and fragmented. We are sector- and stage-agnostic, and leverage our proprietary approaches and data gathering pipelines to uncover market intelligence most relevant to modern businesses and investors. | |
| Founded by an IIT Delhi alumnus, NYU Stern MBA and former NYC investment banker, the firm aims to utilize a strong understanding and know-how of private markets to deliver a compelling value proposition to all participants involved. | |
| Key Responsibilities: | |
| Collaborate with senior leadership to develop and implement ML algorithms to integrate into our applications | |
| Assist in building and optimizing models for various AI applications relating to the company’s objectives | |
| Conduct data collection, analysis and preparation for training machine learning models and developing scorecards and recommendation engines | |
| Assist in deploying and monitoring ML models in a cloud environment (AWS/GCP/Azure) | |
| Improve our internal knowledge base using RAG architecture to make complex private market data searchable | |
| Working on Gen AI applications of open source or proprietary LLMs | |
| Work on NLP projects including sentiment analysis, text classification, etc | |
| Research and implement new AI techniques to improve existing models | |
| Assist in designing and implementing data structures for efficient data processing | |
| Present findings and recommendations to the AI and founding teams and contribute to the overall growth of the company | |
| If you are passionate about AI and ML, and eager to learn and grow in this field, this internship is the perfect opportunity for you to gain valuable hands-on experience and make a real impact. Join us in shaping the future of private markets! | |
| Desired Skills and Experience: | |
| Experience in Python, artificial intelligence, natural language processing (NLP), neural networks, machine learning, deep learning, LLMs and data science acquired through strong academic research in the field or past internships in similar roles | |
| Preferred Qualifications: | |
| Bachelors or Masters in computer science, math, statistics or a related field from reputed institutions with in India or abroad | |
| Candidates nearing graduation or recently graduated are preferred | |
| Compensation: | |
| Base monthly stipend | |
| One-time assured bonus payable at the end of the internship | |
| Performance-linked incentives payable at the end of the internship at the company’s discretion | |
| Location: | |
| Remote",https://media.licdn.com/dms/image/v2/D560BAQGfY7IzJUkZkg/company-logo_100_100/company-logo_100_100/0/1727618037754/hyperqube_ionic_logo?e=1776297600&v=beta&t=__p3HokvIG0Fdd4sbogfOQhdo2KD751FhygnRt9WlLM | |
| AI/ML Intern,Hyperqube Ionic,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| As an AI/ML intern, you will have the opportunity to work on cutting-edge projects at the intersection of artificial intelligence, machine learning and private market investments. We view this internship as a 3–6 month interview for your permanent seat at the table. | |
| You will be using your knowledge of and experience in Python, artificial intelligence, natural language processing (NLP), neural networks, machine learning, LLMs and modern, scalable AI technologies to develop innovative, technology-driven solutions for our company. | |
| Company Overview: | |
| Hyperqube Ionic is at the forefront of developing scalable technology infrastructure redefining how private capital forms conviction, builds trust, and moves into companies. Through our proprietary technology and machine learning algorithms, we uncover hidden signals, standardize information, unlock better decision-making, cull noise, and ensure faster outcomes. | |
| We are pioneering the development of the missing operating system of private markets with the objective of eliminating the outdated practices that make private markets inefficient and fragmented. We are sector- and stage-agnostic, and leverage our proprietary approaches and data gathering pipelines to uncover market intelligence most relevant to modern businesses and investors. | |
| Founded by an IIT Delhi alumnus, NYU Stern MBA and former NYC investment banker, the firm aims to utilize a strong understanding and know-how of private markets to deliver a compelling value proposition to all participants involved. | |
| Key Responsibilities: | |
| Collaborate with senior leadership to develop and implement ML algorithms to integrate into our applications | |
| Assist in building and optimizing models for various AI applications relating to the company’s objectives | |
| Conduct data collection, analysis and preparation for training machine learning models and developing scorecards and recommendation engines | |
| Assist in deploying and monitoring ML models in a cloud environment (AWS/GCP/Azure) | |
| Improve our internal knowledge base using RAG architecture to make complex private market data searchable | |
| Working on Gen AI applications of open source or proprietary LLMs | |
| Work on NLP projects including sentiment analysis, text classification, etc | |
| Research and implement new AI techniques to improve existing models | |
| Assist in designing and implementing data structures for efficient data processing | |
| Present findings and recommendations to the AI and founding teams and contribute to the overall growth of the company | |
| If you are passionate about AI and ML, and eager to learn and grow in this field, this internship is the perfect opportunity for you to gain valuable hands-on experience and make a real impact. Join us in shaping the future of private markets! | |
| Desired Skills and Experience: | |
| Experience in Python, artificial intelligence, natural language processing (NLP), neural networks, machine learning, deep learning, LLMs and data science acquired through strong academic research in the field or past internships in similar roles | |
| Preferred Qualifications: | |
| Bachelors or Masters in computer science, math, statistics or a related field from reputed institutions with in India or abroad | |
| Candidates nearing graduation or recently graduated are preferred | |
| Compensation: | |
| Base monthly stipend | |
| One-time assured bonus payable at the end of the internship | |
| Performance-linked incentives payable at the end of the internship at the company’s discretion | |
| Location: | |
| Remote",N/A | |
| AI/ML Intern,Hyperqube Ionic,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| As an AI/ML intern, you will have the opportunity to work on cutting-edge projects at the intersection of artificial intelligence, machine learning and private market investments. We view this internship as a 3–6 month interview for your permanent seat at the table. | |
| You will be using your knowledge of and experience in Python, artificial intelligence, natural language processing (NLP), neural networks, machine learning, LLMs and modern, scalable AI technologies to develop innovative, technology-driven solutions for our company. | |
| Company Overview: | |
| Hyperqube Ionic is at the forefront of developing scalable technology infrastructure redefining how private capital forms conviction, builds trust, and moves into companies. Through our proprietary technology and machine learning algorithms, we uncover hidden signals, standardize information, unlock better decision-making, cull noise, and ensure faster outcomes. | |
| We are pioneering the development of the missing operating system of private markets with the objective of eliminating the outdated practices that make private markets inefficient and fragmented. We are sector- and stage-agnostic, and leverage our proprietary approaches and data gathering pipelines to uncover market intelligence most relevant to modern businesses and investors. | |
| Founded by an IIT Delhi alumnus, NYU Stern MBA and former NYC investment banker, the firm aims to utilize a strong understanding and know-how of private markets to deliver a compelling value proposition to all participants involved. | |
| Key Responsibilities: | |
| Collaborate with senior leadership to develop and implement ML algorithms to integrate into our applications | |
| Assist in building and optimizing models for various AI applications relating to the company’s objectives | |
| Conduct data collection, analysis and preparation for training machine learning models and developing scorecards and recommendation engines | |
| Assist in deploying and monitoring ML models in a cloud environment (AWS/GCP/Azure) | |
| Improve our internal knowledge base using RAG architecture to make complex private market data searchable | |
| Working on Gen AI applications of open source or proprietary LLMs | |
| Work on NLP projects including sentiment analysis, text classification, etc | |
| Research and implement new AI techniques to improve existing models | |
| Assist in designing and implementing data structures for efficient data processing | |
| Present findings and recommendations to the AI and founding teams and contribute to the overall growth of the company | |
| If you are passionate about AI and ML, and eager to learn and grow in this field, this internship is the perfect opportunity for you to gain valuable hands-on experience and make a real impact. Join us in shaping the future of private markets! | |
| Desired Skills and Experience: | |
| Experience in Python, artificial intelligence, natural language processing (NLP), neural networks, machine learning, deep learning, LLMs and data science acquired through strong academic research in the field or past internships in similar roles | |
| Preferred Qualifications: | |
| Bachelors or Masters in computer science, math, statistics or a related field from reputed institutions with in India or abroad | |
| Candidates nearing graduation or recently graduated are preferred | |
| Compensation: | |
| Base monthly stipend | |
| One-time assured bonus payable at the end of the internship | |
| Performance-linked incentives payable at the end of the internship at the company’s discretion | |
| Location: | |
| Remote",N/A | |
| Data Science Intern,Collegedunia,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| Location: Gurgaon | |
| Mode: Work From Office (WFO) | |
| Duration: 6 months (extendable based on performance) | |
| About the Role | |
| We are looking for a motivated Data Science Intern to support our AI, analytics, and automation initiatives. The | |
| ideal candidate should have strong analytical skills, hands-on experience with Python/ML basics, and a | |
| willingness to explore advanced AI workflows. | |
| Key Responsibilities (KRAs) | |
| 1. Build and maintain deep learning models for analytical, forecasting, and predictive use cases. | |
| 2. Develop Agentic AI workflows and automation pipelines to enhance productivity and system efficiency. | |
| 3. Perform data cleaning, preprocessing, and feature engineering to prepare high-quality datasets. | |
| 4. Collaborate with cross-functional teams to deliver data-driven solutions aligned with business needs. | |
| Requirements | |
| Strong understanding of Python, Machine Learning, and basic Deep Learning (TensorFlow/PyTorch). | |
| Good knowledge of data preprocessing, EDA, and feature engineering. | |
| Familiarity with LLMs, agent-based systems, or automation pipelines (bonus). | |
| Experience with SQL and basic data structures. | |
| Ability to work in a fast-paced team environment and learn quickly. | |
| Good to Have | |
| Prior academic/industry ML projects (NLP, LLMs, automation, etc.). | |
| Knowledge of cloud platforms (AWS/GCP/Azure). | |
| Exposure to MLOps or workflow orchestration tools.",https://media.licdn.com/dms/image/v2/C560BAQHCm62VvmUA0Q/company-logo_100_100/company-logo_100_100/0/1630657086263/collegedunia_logo?e=1776297600&v=beta&t=H5QRjmBdkIx3jtIsLw28KsvEA0QBGBt9RYy9QATNQUA | |
| Data Science Intern,Collegedunia,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| Location: Gurgaon | |
| Mode: Work From Office (WFO) | |
| Duration: 6 months (extendable based on performance) | |
| About the Role | |
| We are looking for a motivated Data Science Intern to support our AI, analytics, and automation initiatives. The | |
| ideal candidate should have strong analytical skills, hands-on experience with Python/ML basics, and a | |
| willingness to explore advanced AI workflows. | |
| Key Responsibilities (KRAs) | |
| 1. Build and maintain deep learning models for analytical, forecasting, and predictive use cases. | |
| 2. Develop Agentic AI workflows and automation pipelines to enhance productivity and system efficiency. | |
| 3. Perform data cleaning, preprocessing, and feature engineering to prepare high-quality datasets. | |
| 4. Collaborate with cross-functional teams to deliver data-driven solutions aligned with business needs. | |
| Requirements | |
| Strong understanding of Python, Machine Learning, and basic Deep Learning (TensorFlow/PyTorch). | |
| Good knowledge of data preprocessing, EDA, and feature engineering. | |
| Familiarity with LLMs, agent-based systems, or automation pipelines (bonus). | |
| Experience with SQL and basic data structures. | |
| Ability to work in a fast-paced team environment and learn quickly. | |
| Good to Have | |
| Prior academic/industry ML projects (NLP, LLMs, automation, etc.). | |
| Knowledge of cloud platforms (AWS/GCP/Azure). | |
| Exposure to MLOps or workflow orchestration tools.",N/A | |
| Data Science Intern,Collegedunia,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| Location: Gurgaon | |
| Mode: Work From Office (WFO) | |
| Duration: 6 months (extendable based on performance) | |
| About the Role | |
| We are looking for a motivated Data Science Intern to support our AI, analytics, and automation initiatives. The | |
| ideal candidate should have strong analytical skills, hands-on experience with Python/ML basics, and a | |
| willingness to explore advanced AI workflows. | |
| Key Responsibilities (KRAs) | |
| 1. Build and maintain deep learning models for analytical, forecasting, and predictive use cases. | |
| 2. Develop Agentic AI workflows and automation pipelines to enhance productivity and system efficiency. | |
| 3. Perform data cleaning, preprocessing, and feature engineering to prepare high-quality datasets. | |
| 4. Collaborate with cross-functional teams to deliver data-driven solutions aligned with business needs. | |
| Requirements | |
| Strong understanding of Python, Machine Learning, and basic Deep Learning (TensorFlow/PyTorch). | |
| Good knowledge of data preprocessing, EDA, and feature engineering. | |
| Familiarity with LLMs, agent-based systems, or automation pipelines (bonus). | |
| Experience with SQL and basic data structures. | |
| Ability to work in a fast-paced team environment and learn quickly. | |
| Good to Have | |
| Prior academic/industry ML projects (NLP, LLMs, automation, etc.). | |
| Knowledge of cloud platforms (AWS/GCP/Azure). | |
| Exposure to MLOps or workflow orchestration tools.",N/A | |
| "Data Science Internship in Noida, Gurgaon, Delhi, Faridabad, Ghaziabad",MCUBE AI PRIVATE LIMITED,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| This job is sourced from a job board. Learn More | |
| work location - Gurgaon | |
| Selected Intern's Day-to-day Responsibilities Include | |
| Work closely with our team of data scientists to analyze and interpret complex data sets. | |
| Research emerging trends in data science and AI to drive innovation. | |
| Assist in data cleaning, preprocessing, and visualization to extract actionable insights. | |
| Present findings and recommendations to senior management clearly and concisely. | |
| Develop and implement machine learning models to improve our AI algorithms. | |
| Utilize NLP techniques to enhance our natural language processing capabilities. | |
| Collaborate with cross-functional teams to integrate AI solutions into our products. | |
| About Company: We are an AI native product development organization, where we design and ship fully AI-native products - from concept to production. Whether we are building an AI-powered app, internal platform, automation suite, or enterprise tool, we engineer systems that treat AI as the core engine, not an add-on. | |
| Desired Skills and Experience | |
| Natural Language Processing (NLP), Deep Learning, Artificial intelligence, Python, SQL, Data Analytics, Machine Learning, Data Science",https://media.licdn.com/dms/image/v2/D560BAQEyDj86mzIOjA/company-logo_100_100/B56ZyJx4.fJUAU-/0/1771838083496?e=1776297600&v=beta&t=6bpDxSYgoD0n6ezP8Auy-55nOVNgmcT27btciSk0hI4 | |
| "Data Science Internship in Noida, Gurgaon, Delhi, Faridabad, Ghaziabad",MCUBE AI PRIVATE LIMITED,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| This job is sourced from a job board. Learn More | |
| work location - Gurgaon | |
| Selected Intern's Day-to-day Responsibilities Include | |
| Work closely with our team of data scientists to analyze and interpret complex data sets. | |
| Research emerging trends in data science and AI to drive innovation. | |
| Assist in data cleaning, preprocessing, and visualization to extract actionable insights. | |
| Present findings and recommendations to senior management clearly and concisely. | |
| Develop and implement machine learning models to improve our AI algorithms. | |
| Utilize NLP techniques to enhance our natural language processing capabilities. | |
| Collaborate with cross-functional teams to integrate AI solutions into our products. | |
| About Company: We are an AI native product development organization, where we design and ship fully AI-native products - from concept to production. Whether we are building an AI-powered app, internal platform, automation suite, or enterprise tool, we engineer systems that treat AI as the core engine, not an add-on. | |
| Desired Skills and Experience | |
| Natural Language Processing (NLP), Deep Learning, Artificial intelligence, Python, SQL, Data Analytics, Machine Learning, Data Science",N/A | |
| "Data Science Internship in Noida, Gurgaon, Delhi, Faridabad, Ghaziabad",MCUBE AI PRIVATE LIMITED,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| This job is sourced from a job board. Learn More | |
| work location - Gurgaon | |
| Selected Intern's Day-to-day Responsibilities Include | |
| Work closely with our team of data scientists to analyze and interpret complex data sets. | |
| Research emerging trends in data science and AI to drive innovation. | |
| Assist in data cleaning, preprocessing, and visualization to extract actionable insights. | |
| Present findings and recommendations to senior management clearly and concisely. | |
| Develop and implement machine learning models to improve our AI algorithms. | |
| Utilize NLP techniques to enhance our natural language processing capabilities. | |
| Collaborate with cross-functional teams to integrate AI solutions into our products. | |
| About Company: We are an AI native product development organization, where we design and ship fully AI-native products - from concept to production. Whether we are building an AI-powered app, internal platform, automation suite, or enterprise tool, we engineer systems that treat AI as the core engine, not an add-on. | |
| Desired Skills and Experience | |
| Natural Language Processing (NLP), Deep Learning, Artificial intelligence, Python, SQL, Data Analytics, Machine Learning, Data Science",https://media.licdn.com/dms/image/v2/D560BAQEyDj86mzIOjA/company-logo_100_100/B56ZyJx4.fJUAU-/0/1771838083496?e=1776297600&v=beta&t=6bpDxSYgoD0n6ezP8Auy-55nOVNgmcT27btciSk0hI4 | |
| "Data Science Internship in Noida, Gurgaon, Delhi, Faridabad, Ghaziabad",MCUBE AI PRIVATE LIMITED,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| This job is sourced from a job board. Learn More | |
| work location - Gurgaon | |
| Selected Intern's Day-to-day Responsibilities Include | |
| Work closely with our team of data scientists to analyze and interpret complex data sets. | |
| Research emerging trends in data science and AI to drive innovation. | |
| Assist in data cleaning, preprocessing, and visualization to extract actionable insights. | |
| Present findings and recommendations to senior management clearly and concisely. | |
| Develop and implement machine learning models to improve our AI algorithms. | |
| Utilize NLP techniques to enhance our natural language processing capabilities. | |
| Collaborate with cross-functional teams to integrate AI solutions into our products. | |
| About Company: We are an AI native product development organization, where we design and ship fully AI-native products - from concept to production. Whether we are building an AI-powered app, internal platform, automation suite, or enterprise tool, we engineer systems that treat AI as the core engine, not an add-on. | |
| Desired Skills and Experience | |
| Natural Language Processing (NLP), Deep Learning, Artificial intelligence, Python, SQL, Data Analytics, Machine Learning, Data Science",N/A | |
| "AI Researcher, Speech & Audio, Intern | Josh Talks",Josh Talks,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| This job is sourced from a job board. Learn More | |
| form :https://forms.gle/ncGqEJrJDvEDhXtL7 | |
| AI Researcher, Speech & Audio, Intern - | |
| Internship Opportunity at JoshTalks AI Lab | |
| (ai.joshtalks.com) | |
| Location: Gurgaon, India | |
| Type: Full-time Internship (6–12 months) | |
| Who: Final-year engineering students or recent graduates passionate about AI/ML | |
| in speech | |
| About Us | |
| At JoshTalks AI Lab, we believe that voice will be the primary medium of interaction | |
| between man and machine. Our mission is simple yet ambitious: | |
| Help machines talk like humans. | |
| Build the benchmarks and datasets that become the backbone of global | |
| progress in speech AI. | |
| Drive improvements not just through compute or algorithms — but through | |
| high-quality, diverse, real-world data. | |
| Our datasets today power some of the largest and most widely used speech | |
| models in the world (you’ve definitely used them, even if we can’t name them | |
| 😉). | |
| What You’ll Work On | |
| This is not a “just another internship.” You’ll be directly contributing to the global | |
| Race To Perfect Speech AI | |
| Benchmarking the world’s speech models | |
| ○ Design and run evaluations for ASR and speech-to-speech systems. | |
| ○ Create benchmarks that will guide top AI labs on where their models | |
| fail and where they shine. | |
| Modeling & Fine-Tuning | |
| ○ Fine-tune speech recognition systems (like Whisper/wav2vec2) to push | |
| Word Error Rates toward ~5%. | |
| ○ Experiment with multilingual, code-switched, and noisy speech | |
| to mimic real-world conditions. | |
| Impact at Scale | |
| ○ Your work won’t just sit in a paper. It will influence how the | |
| world’s largest AI models get built, tested, and improved. | |
| Who We’re Looking For | |
| Final-year undergraduates (B.Tech/B.E.) in CSE, EE, AI/ML, or related fields. | |
| Strong interest in speech, audio, NLP, or multimodal AI. | |
| Hands-on experience in one or more of: | |
| ○ Fine-tuning speech or language models (Whisper, wav2vec2, | |
| HuBERT, SER, etc.) | |
| ○ Building speech-driven projects (assistants, classifiers, chatbots, | |
| SER systems) | |
| ○ Working with PyTorch, TensorFlow, or Hugging Face transformers. | |
| Bonus: past projects on GitHub, Kaggle, or research papers. | |
| Why Join Us | |
| Ownership: Even as a final-year student, you’ll get the chance to own | |
| problems of global importance — from reducing ASR word error rates toward | |
| 5% to building benchmarks that influence how the next generation of | |
| Speech-to-speech Models Are Developed. These Are Not Side Projects | |
| the problems you’ll work on may define how billions of people interact | |
| with machines in the future. | |
| Front-row seat in speech AI: Your work will shape benchmarks and datasets | |
| used by the world’s top model labs. | |
| Learning: Work with experts solving speech challenges across 20+ | |
| Indian languages and noisy, real-world audio. | |
| Impactful projects: The benchmarks and models you help build will | |
| set direction for global AI progress. | |
| Startup energy, global scale: Small team, big impact — perfect for ambitious | |
| builders. | |
| Co-Authorship: If any of the work you contribute to is published as a paper, | |
| benchmark report, or dataset release, you will be credited as a co-author. | |
| This means your contributions won’t just stay inside the lab — they’ll be | |
| visible to the wider research community and part of the academic and | |
| industry record. | |
| Details | |
| Location: Gurgaon (on-site preferred for collaboration) | |
| Duration: 6–12 months | |
| Type: Paid Internship (full-time) | |
| Start Date: Flexible for final-year students (aligns with academic calendar) | |
| If you’re someone who dreams of making speech AI as natural as human | |
| conversation, this is your chance to work on the real frontier. Super interested? | |
| Skills:- Machine Learning (ML)",https://media.licdn.com/dms/image/v2/C4D0BAQEhXz8cBVn4Vw/company-logo_100_100/company-logo_100_100/0/1672770926771/joshtalks_logo?e=1776297600&v=beta&t=4glboJZMLKY_sJS8edDbb-uZFG6cDzkc9lquXtMkABk | |
| "AI Researcher, Speech & Audio, Intern | Josh Talks",Josh Talks,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| This job is sourced from a job board. Learn More | |
| form :https://forms.gle/ncGqEJrJDvEDhXtL7 | |
| AI Researcher, Speech & Audio, Intern - | |
| Internship Opportunity at JoshTalks AI Lab | |
| (ai.joshtalks.com) | |
| Location: Gurgaon, India | |
| Type: Full-time Internship (6–12 months) | |
| Who: Final-year engineering students or recent graduates passionate about AI/ML | |
| in speech | |
| About Us | |
| At JoshTalks AI Lab, we believe that voice will be the primary medium of interaction | |
| between man and machine. Our mission is simple yet ambitious: | |
| Help machines talk like humans. | |
| Build the benchmarks and datasets that become the backbone of global | |
| progress in speech AI. | |
| Drive improvements not just through compute or algorithms — but through | |
| high-quality, diverse, real-world data. | |
| Our datasets today power some of the largest and most widely used speech | |
| models in the world (you’ve definitely used them, even if we can’t name them | |
| 😉). | |
| What You’ll Work On | |
| This is not a “just another internship.” You’ll be directly contributing to the global | |
| Race To Perfect Speech AI | |
| Benchmarking the world’s speech models | |
| ○ Design and run evaluations for ASR and speech-to-speech systems. | |
| ○ Create benchmarks that will guide top AI labs on where their models | |
| fail and where they shine. | |
| Modeling & Fine-Tuning | |
| ○ Fine-tune speech recognition systems (like Whisper/wav2vec2) to push | |
| Word Error Rates toward ~5%. | |
| ○ Experiment with multilingual, code-switched, and noisy speech | |
| to mimic real-world conditions. | |
| Impact at Scale | |
| ○ Your work won’t just sit in a paper. It will influence how the | |
| world’s largest AI models get built, tested, and improved. | |
| Who We’re Looking For | |
| Final-year undergraduates (B.Tech/B.E.) in CSE, EE, AI/ML, or related fields. | |
| Strong interest in speech, audio, NLP, or multimodal AI. | |
| Hands-on experience in one or more of: | |
| ○ Fine-tuning speech or language models (Whisper, wav2vec2, | |
| HuBERT, SER, etc.) | |
| ○ Building speech-driven projects (assistants, classifiers, chatbots, | |
| SER systems) | |
| ○ Working with PyTorch, TensorFlow, or Hugging Face transformers. | |
| Bonus: past projects on GitHub, Kaggle, or research papers. | |
| Why Join Us | |
| Ownership: Even as a final-year student, you’ll get the chance to own | |
| problems of global importance — from reducing ASR word error rates toward | |
| 5% to building benchmarks that influence how the next generation of | |
| Speech-to-speech Models Are Developed. These Are Not Side Projects | |
| the problems you’ll work on may define how billions of people interact | |
| with machines in the future. | |
| Front-row seat in speech AI: Your work will shape benchmarks and datasets | |
| used by the world’s top model labs. | |
| Learning: Work with experts solving speech challenges across 20+ | |
| Indian languages and noisy, real-world audio. | |
| Impactful projects: The benchmarks and models you help build will | |
| set direction for global AI progress. | |
| Startup energy, global scale: Small team, big impact — perfect for ambitious | |
| builders. | |
| Co-Authorship: If any of the work you contribute to is published as a paper, | |
| benchmark report, or dataset release, you will be credited as a co-author. | |
| This means your contributions won’t just stay inside the lab — they’ll be | |
| visible to the wider research community and part of the academic and | |
| industry record. | |
| Details | |
| Location: Gurgaon (on-site preferred for collaboration) | |
| Duration: 6–12 months | |
| Type: Paid Internship (full-time) | |
| Start Date: Flexible for final-year students (aligns with academic calendar) | |
| If you’re someone who dreams of making speech AI as natural as human | |
| conversation, this is your chance to work on the real frontier. Super interested? | |
| Skills:- Machine Learning (ML)",N/A | |
| Computer Vision Intern,Flick2Know,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| We are looking for a Computer Vision Intern to assist in building and refining our image recognition pipeline. The role will start with dataset management—image collection, annotation validation, dataset cleaning, and preprocessing. Once the foundational data work is complete, you’ll get hands-on exposure to model training, augmentation, and evaluation, contributing directly to our production-ready pipeline. | |
| Responsibilities | |
| For one in the Seat: | |
| Organize, clean, and preprocess large-scale retail image datasets. | |
| Validate and manage annotations (bounding boxes, class labels, segmentation masks if applicable) using tools like Roboflow or CVAT or LabelImg. | |
| Apply augmentation techniques and prepare datasets for training. | |
| Support in training YOLOv5/YOLOv8-based models on custom datasets. | |
| Run model evaluations (Precision, Recall, F1 Score, SKU-level accuracy). | |
| Collaborate with the product team to improve real-world inference quality. | |
| Document the dataset pipeline and share insights for improving data quality. | |
| Must Have | |
| Who we're looking for: | |
| Basic understanding of Computer Vision concepts (Object Detection, Classification) | |
| Familiarity with Python (OpenCV, Pandas, NumPy) | |
| Knowledge of image annotation tools (Roboflow, LabelImg, CVAT, etc.) | |
| Ability to manage and organise large datasets | |
| Good To Have | |
| Experience with YOLOv5 or YOLOv8 (Training, Inference, Fine-tuning) | |
| Exposure to image augmentation techniques (Albumentations, etc.) | |
| Understanding of retail/commercial shelf datasets or product detection problems | |
| Previous internship or project experience in computer vision is a plus",https://media.licdn.com/dms/image/v2/C4E0BAQEgY_MrJX98Ww/company-logo_100_100/company-logo_100_100/0/1631348826733?e=1776297600&v=beta&t=TzrkyqRv7ENwPpFDCL1hxmDLYHgh8WOiDT92ZEVZ5iA | |
| Computer Vision Intern,Flick2Know,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| We are looking for a Computer Vision Intern to assist in building and refining our image recognition pipeline. The role will start with dataset management—image collection, annotation validation, dataset cleaning, and preprocessing. Once the foundational data work is complete, you’ll get hands-on exposure to model training, augmentation, and evaluation, contributing directly to our production-ready pipeline. | |
| Responsibilities | |
| For one in the Seat: | |
| Organize, clean, and preprocess large-scale retail image datasets. | |
| Validate and manage annotations (bounding boxes, class labels, segmentation masks if applicable) using tools like Roboflow or CVAT or LabelImg. | |
| Apply augmentation techniques and prepare datasets for training. | |
| Support in training YOLOv5/YOLOv8-based models on custom datasets. | |
| Run model evaluations (Precision, Recall, F1 Score, SKU-level accuracy). | |
| Collaborate with the product team to improve real-world inference quality. | |
| Document the dataset pipeline and share insights for improving data quality. | |
| Must Have | |
| Who we're looking for: | |
| Basic understanding of Computer Vision concepts (Object Detection, Classification) | |
| Familiarity with Python (OpenCV, Pandas, NumPy) | |
| Knowledge of image annotation tools (Roboflow, LabelImg, CVAT, etc.) | |
| Ability to manage and organise large datasets | |
| Good To Have | |
| Experience with YOLOv5 or YOLOv8 (Training, Inference, Fine-tuning) | |
| Exposure to image augmentation techniques (Albumentations, etc.) | |
| Understanding of retail/commercial shelf datasets or product detection problems | |
| Previous internship or project experience in computer vision is a plus",N/A | |
| Computer Vision Intern,FieldAssist,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| We are looking for a Computer Vision Intern to assist in building and refining our image recognition pipeline. The role will start with dataset management—image collection, annotation validation, dataset cleaning, and preprocessing. Once the foundational data work is complete, you’ll get hands-on exposure to model training, augmentation, and evaluation, contributing directly to our production-ready pipeline. | |
| For one in the Seat: | |
| Responsibilities | |
| Organize, clean, and preprocess large-scale retail image datasets. | |
| Validate and manage annotations (bounding boxes, class labels, segmentation masks if applicable) using tools like Roboflow or CVAT or LabelImg. | |
| Apply augmentation techniques and prepare datasets for training. | |
| Support in training YOLOv5/YOLOv8-based models on custom datasets. | |
| Run model evaluations (Precision, Recall, F1 Score, SKU-level accuracy). | |
| Collaborate with the product team to improve real-world inference quality. | |
| Document the dataset pipeline and share insights for improving data quality. | |
| Who we're looking for: | |
| Must Have: | |
| Basic understanding of Computer Vision concepts (Object Detection, Classification) | |
| Familiarity with Python (OpenCV, Pandas, NumPy) | |
| Knowledge of image annotation tools (Roboflow, LabelImg, CVAT, etc.) | |
| Ability to manage and organise large datasets | |
| Good to have: | |
| Experience with YOLOv5 or YOLOv8 (Training, Inference, Fine-tuning) | |
| Exposure to image augmentation techniques (Albumentations, etc.) | |
| Understanding of retail/commercial shelf datasets or product detection problems | |
| Previous internship or project experience in computer vision is a plus",https://media.licdn.com/dms/image/v2/C4E0BAQGmAYOqBR5fMQ/company-logo_100_100/company-logo_100_100/0/1630614064062/fieldassist_logo?e=1776297600&v=beta&t=437bxOlGDi91AmCPu1tbAePGWHYdkhagMtWMHOraqY4 | |
| Computer Vision Intern,FieldAssist,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| We are looking for a Computer Vision Intern to assist in building and refining our image recognition pipeline. The role will start with dataset management—image collection, annotation validation, dataset cleaning, and preprocessing. Once the foundational data work is complete, you’ll get hands-on exposure to model training, augmentation, and evaluation, contributing directly to our production-ready pipeline. | |
| For one in the Seat: | |
| Responsibilities | |
| Organize, clean, and preprocess large-scale retail image datasets. | |
| Validate and manage annotations (bounding boxes, class labels, segmentation masks if applicable) using tools like Roboflow or CVAT or LabelImg. | |
| Apply augmentation techniques and prepare datasets for training. | |
| Support in training YOLOv5/YOLOv8-based models on custom datasets. | |
| Run model evaluations (Precision, Recall, F1 Score, SKU-level accuracy). | |
| Collaborate with the product team to improve real-world inference quality. | |
| Document the dataset pipeline and share insights for improving data quality. | |
| Who we're looking for: | |
| Must Have: | |
| Basic understanding of Computer Vision concepts (Object Detection, Classification) | |
| Familiarity with Python (OpenCV, Pandas, NumPy) | |
| Knowledge of image annotation tools (Roboflow, LabelImg, CVAT, etc.) | |
| Ability to manage and organise large datasets | |
| Good to have: | |
| Experience with YOLOv5 or YOLOv8 (Training, Inference, Fine-tuning) | |
| Exposure to image augmentation techniques (Albumentations, etc.) | |
| Understanding of retail/commercial shelf datasets or product detection problems | |
| Previous internship or project experience in computer vision is a plus",N/A | |
| Face Recognition Engineer,Unified Consultancy Services,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| Job Title | |
| Face Recognition Engineer – HRMS & HRIS | |
| Location: | |
| Remote / Onsite (Flexible) | |
| Employment Type: Full-time - INTERN | |
| About Unified Consultancy Services | |
| Unified Consultancy Services is a next-gen technology and consulting company specializing in AI, automation, and enterprise digital transformation. We are building cutting-edge solutions in HRMS (Human Resource Management Systems) and HRIS (Human Resource Information Systems) with integrated AI-driven face recognition for secure, seamless, and efficient workforce management. | |
| Role Overview | |
| We are seeking a skilled Face Recognition Engineer with expertise in OpenCV, Python, and AI/ML-based biometric systems to design, develop, and integrate face recognition modules into our HRMS & HRIS platforms. The role involves working closely with product and engineering teams to deliver robust, scalable, and secure identity verification and attendance-tracking systems. | |
| Key Responsibilities | |
| Design and implement face recognition algorithms using OpenCV, Python, and deep learning frameworks. | |
| Develop and optimize real-time face detection, verification, and recognition pipelines. | |
| Integrate biometric authentication into HRMS & HRIS applications (attendance, KYC, employee login). | |
| Ensure high accuracy, performance, and security in biometric verification. | |
| Research and apply state-of-the-art computer vision techniques for face recognition. | |
| Collaborate with backend developers to integrate APIs with enterprise HR platforms. | |
| Conduct testing, debugging, and performance tuning for biometric modules. | |
| Stay updated with AI, computer vision, and HR technology trends. | |
| Required Skills & Qualifications | |
| Bachelor’s/Master’s degree in Computer Science, AI, Data Science, or related field. | |
| Strong hands-on experience with OpenCV, Python, NumPy, Pandas, and Scikit-learn. | |
| Proficiency in deep learning frameworks (TensorFlow, Keras, or PyTorch). | |
| Experience with face detection, recognition, and liveness detection algorithms. | |
| Knowledge of HRMS & HRIS systems and how biometric modules integrate. | |
| Familiarity with REST APIs, cloud deployment (AWS, Azure, GCP). | |
| Strong understanding of data privacy, GDPR, and biometric security standards. | |
| Excellent problem-solving skills and ability to work in an agile team. | |
| Preferred Skills (Good To Have) | |
| Experience in edge AI deployment (Raspberry Pi, Jetson Nano, mobile apps). | |
| Familiarity with Docker, Kubernetes, and CI/CD pipelines. | |
| Knowledge of employee lifecycle management systems (HRIS/HRMS workflows). | |
| Previous experience with enterprise-scale biometric attendance systems. | |
| What We Offer | |
| Opportunity to work on cutting-edge AI in HR tech. | |
| Collaborative and innovation-driven environment. | |
| Career growth with exposure to AI, HRMS, HRIS, and enterprise security. | |
| Competitive salary and performance-based incentives.",https://media.licdn.com/dms/image/v2/D560BAQFlgio_qyNdJg/company-logo_100_100/B56ZsC8nG_JQAQ-/0/1765281002733/ufsnetworks_logo?e=1776297600&v=beta&t=cwNJqKgCSMnab2brwWLMDcf-FDMWk2_kWc0gXlqYuvM | |
| AI Engineer,Taxmann,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| Job Description | |
| About the Role | |
| We are looking for a passionate and driven AI Engineer (Intern/Fresher/Experienced) with hands-on experience or strong academic exposure in RAG (Retrieval-Augmented Generation) approaches. You will work closely with our AI and product teams to design, prototype, and optimize intelligent solutions that integrate language models with structured/unstructured knowledge sources. This is a great opportunity to build impactful AI systems and work with modern NLP tools in real-world production environments. | |
| Responsibilities | |
| Design and build AI applications using RAG-based architecturesFine-tune and integrate LLMs (eg, OpenAI, LLaMA, Mistral, etc) with external data sources | |
| Build and optimize pipelines for document ingestion, chunking, vector embedding, and retrieval | |
| Implement and experiment with tools like LangChain, Haystack, Weaviate, Pinecone, Chroma, FAISS | |
| Develop and maintain RESTful APIs and web applications using Python frameworks such as Flask or FastAPI | |
| Collaborate with frontend/backend teams to integrate AI into live products | |
| Conduct evaluations, benchmark performance, and recommend improvements | |
| Work with team leads to convert PoCs into scalable solutions | |
| For Experienced (2+ Years): | |
| Proven experience in building or contributing to AI products using RAG architecture | |
| Strong proficiency in Python for data manipulation and API development | |
| Experience in RESTful API development using Flask or FastAPI | |
| Solid knowledge of SQL, data analytics, and Power BI | |
| Hands-on experience with version control (Git) and deployment tools | |
| Exposure to cloud platforms such as AWS is a strong plus | |
| Excellent problem-solving and communication skills | |
| What You'll Gain | |
| Opportunity to work on cutting-edge AI projects with real-world users | |
| Exposure to both product delivery and research-level challenges | |
| Mentorship from experienced AI Engineers and Product Leads | |
| Flat team structure, creative freedom, and a learning-oriented culture | |
| Job Type: Full-Time Internship | |
| Location: New Delhi (Work from Office)",https://media.licdn.com/dms/image/v2/D560BAQHlrEuQG1w8uA/company-logo_100_100/B56Zy8QaZdHUAQ-/0/1772684945477/taxmann_logo?e=1776297600&v=beta&t=IlmXLLOOH5HYOrLR-ZzV2G644lZ_GpLJ8RCcmNvzvkk | |
| Artificial Intelligence Intern,Zoo Media,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| AI Developer Intern (Pathway to Junior Developer) | |
| Open Roles: 2 Positions | |
| About the Role | |
| We are looking for two curious and driven AI Developer Interns to join our engineering team at an exciting stage of building AI-powered products and internal tools. | |
| This is not a typical internship. From day one, you will be contributing to real systems - integrating large language models, building product features, and shipping production-ready code alongside experienced engineers. | |
| This role includes a structured progression plan, where high-performing interns can transition into a full-time Junior Developer role within 120 days. | |
| What You’ll Work On | |
| AI & LLM Integration | |
| Build and iterate on prompt pipelines using APIs such as OpenAI, Anthropic Claude, and open-source models | |
| Integrate LLM capabilities into product features such as summarisation, generation, classification, and retrieval | |
| Experiment with RAG (Retrieval-Augmented Generation) architectures and vector databases | |
| Evaluate model outputs and optimise prompts for quality, cost, and latency | |
| Use modern AI-assisted development tools such as Cursor, GitHub Copilot, and Claude Code | |
| Full-Stack Development | |
| Contribute to a Next.js-based full-stack application | |
| Build and maintain API routes, backend logic, and integrations | |
| Write clean, well-tested code and participate in code reviews | |
| Support deployment pipelines using Docker and CI/CD tooling | |
| Who We’re Looking For | |
| Essential | |
| Comfortable writing JavaScript or TypeScript | |
| Curious about AI, LLMs, and emerging developer tooling | |
| Able to learn quickly and work independently when given direction | |
| Comfortable using Git and collaborating in a team codebase | |
| Strong written communication skills | |
| Nice to Have | |
| Experience with React or Next.js | |
| Exposure to LLM APIs, LangChain, or LlamaIndex | |
| Familiarity with Docker or Linux environments | |
| Personal projects, open-source contributions, or a portfolio | |
| Currently studying or recently graduated in Computer Science, Software Engineering, or related fields | |
| What We Offer | |
| A real engineering role - not a support internship | |
| Direct mentorship from experienced engineers | |
| Access to AI tooling, API credits, and learning resources | |
| Opportunity to ship production-level features | |
| Structured progression plan with the opportunity to become a Junior Developer within 60–120 days | |
| Growth Path | |
| This internship includes a structured 5-phase progression plan covering: | |
| Codebase onboarding and first pull requests | |
| Independent feature development | |
| Ownership of modules or integrations | |
| Production deployments | |
| Transition to a Junior Developer role for strong performers | |
| Progression is based on demonstrated capability, not just time. | |
| How to Apply | |
| Please send your resume along with a short note telling us: | |
| What you’ve built | |
| What you’re currently learning about AI | |
| Why this role interests you | |
| Include links to any GitHub repositories, projects, or portfolios you’d like us to see. | |
| Kindly email your application to careers@zoomedia.in with the subject line “Name – AI Developer Intern.” | |
| Applications will be reviewed on a rolling basis, and we encourage early-career developers who are passionate about AI to apply.",https://media.licdn.com/dms/image/v2/D4D0BAQHZ_P2DkI6MEQ/company-logo_100_100/company-logo_100_100/0/1666351483697/zoomedia_network_logo?e=1776297600&v=beta&t=S-P5TPTHkaH95Y3_BpK49e6aQfaHFXNF-zAZ45LRZ8A | |
| "Data Science Intern, 2026",Data Workers,https://www.linkedin.com/jobs/search-results/,https://www.linkedin.com/jobs/search-results/,"About the job | |
| Company | |
| Data Workers revolutionizes data management by automating tasks and reducing data operation times to less than five minutes. Leveraging specialized MCP servers, each agent is tailored for specific data processes, ensuring precise and efficient workflows. With seamless integration via a single command, Data Workers offers innovative solutions to simplify and expedite data operations for users across multiple domains. | |
| Role Description | |
| This is a remote internship role as a Data Science Intern, 2026. The intern will be responsible for conducting data analysis, assisting with data analytics projects, applying statistical techniques, and contributing to data-driven decision-making processes. Additional duties may include developing and improving data science models, supporting analytical reporting, and collaborating with team members on various data science initiatives. | |
| Qualifications | |
| Proficiency in Data Science, Data Analytics, and Data Analysis methods | |
| Strong foundation in Statistics and Analytical Skills | |
| Familiarity with programming languages and tools used for data science such as Python, R, or SQL is a plus | |
| Excellent problem-solving and critical-thinking abilities | |
| Effective communication skills for presenting data insights | |
| Currently pursuing or recently completed a degree in Data Science, Computer Science, Mathematics, Statistics, or a related field",https://media.licdn.com/dms/image/v2/D4E0BAQFPFBdpaLPfKw/company-logo_100_100/B4EZ0nlh7EJUAQ-/0/1774485643823/data_workers_proj_logo?e=1776297600&v=beta&t=D-kBgwx2-mVlKFsmJuE4h4_svO6TC3-TwqTLogEEpGU | |