Responsibilities : - Design and implement advanced solutions utilizing Large Language Models (LLMs). - Demonstrate self-driven initiative by taking ownership and creating end-to-end solutions. - Conduct research and stay informed about the latest developments in generative AI and LLMs. - Develop and maintain code libraries, tools, and frameworks to support generative AI development. - Participate in code reviews and contribute to maintaining high code quality standards. - Engage in the entire software development lifecycle, from design and testing to deployment and maintenance. - Collaborate closely with cross-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility. - Possess strong analytical and problem-solving skills. - Demonstrate excellent communication skills and the ability to work effectively in a team environment. Primary Skills : - Natural Language Processing (NLP) : Hands-on experience in use case classification, topic modeling, Q&A and chatbots, search, Document AI, summarization, and content generation. - Computer Vision and Audio : Hands-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis. - Generative AI : a. Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. b. Familiarity with Open-source LLMs, including tools like TensorFlow/Pytorch and huggingface. Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization. - Cloud : Hands-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. - Application Development : Proficiency in Python, Docker, FastAPI/Django/Flask, and Git.