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| Job Description | |
| Contribute to the design and implementation of state-of-the-art AI solutions. | |
| Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI. | |
| Collaborate with stakeholders to identify business opportunities and define AI project goals. | |
| Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. | |
| Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases. | |
| Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. | |
| Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. | |
| Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. | |
| Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. | |
| Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. | |
| Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. | |
| Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. | |
| Ensure compliance with data privacy, security, and ethical considerations in AI applications. | |
| Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. | |
| Generative AI | |