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Mid-level data scientist title, metro location, and broad applicant pool balanced by niche GenAI skills.
High because role mandates specialized generative AI, LLM, and ML model fine-tuning expertise.
High due to mandatory LLM, finetuning, RLHF, cloud, and production deployment skills.
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Design and implement advanced Large Language Model (LLM)-based solutions with end-to-end ownership.
Develop, maintain, and deploy generative AI code libraries, tools, and frameworks throughout the software development lifecycle.
Collaborate with cross-functional teams to align technical solutions with product roadmaps and integrate AI software into core systems.
Hands-on experience with Natural Language Processing (NLP) use cases or Computer Vision and Audio AI.
Proficiency with generative AI SaaS LLMs (e.g., LangChain, llama index, vector DBs) and cloud AI platforms like Azure OpenAI, Google Vertex AI, AWS Bedrock.
Experience in Python programming, application development frameworks (FastAPI, Django, Flask), Docker, and Git.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in end-to-end development and deployment of generative AI solutions leveraging both SaaS and open-source LLM tools and frameworks.
Comfortable working across cloud platforms (Azure, AWS, GCP) and optimizing AI models with advanced techniques such as quantization, fine-tuning (PEFT, RLHF), and data annotation workflows.
Able to collaborate closely with cross-functional teams to integrate AI capabilities into product systems and contribute to strategic roadmaps.