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Job Description
Structured overview of role & requirementsAbout This Role
Design and implement advanced Large Language Model (LLM)-based generative AI solutions end-to-end.
Develop and maintain code libraries, tools, and frameworks to support generative AI projects, including participation in code reviews to ensure high code quality.
Collaborate with cross-functional teams throughout the software development lifecycle to align roadmaps and integrate solutions into core systems.
Minimum Requirements
Hands-on experience with Natural Language Processing (NLP) use cases and/or Computer Vision and Audio AI techniques.
Proficiency with SaaS LLMs and generative AI tools including Lang chain, llama index, prompt engineering, and experience with Azure OpenAI, Google Vertex AI, or AWS Bedrock.
Experience with open-source LLM frameworks such as TensorFlow/PyTorch and huggingface, including techniques like LLM fine-tuning and GPU utilization.
Proficiency in Python programming, Docker, frameworks like FastAPI/Django/Flask, Git, and practical experience with cloud platforms (Azure, AWS, or GCP); cloud certification preferred.
Ideal Candidate Profile
Experienced working with scalable generative AI architectures and LLM deployment in production environments.
Technically skilled in integrating LLM and generative AI technologies into cross-functional projects with an emphasis on maintainability and quality.
Familiar with research and application of latest generative AI trends, able to bridge experimental solutions with practical software development demands.