Description

Design, develop, and deploy proprietary AI workflows and end-to-end chatbots for internal scientists and stakeholders.

Responsibilities

• Architect private AI solutions using LLM models and RAG pipelines within cloud environments.
• Define business use cases for tailored GenAI and Copilot solutions with senior leadership.
• Implement solutions involving prompt engineering and document specification.
• Establish design principles, architecture standards, and best practices aligned with IT strategy.
• Collaborate with cross-functional teams to identify opportunities for LLMs to enhance productivity.

Required Skills

• 5+ years of experience in data science, AI/ML, or enterprise software development.
• Proven experience with Large Language Models (LLMs) and Retrieval Augmented Generation (RAG) pipelines.
• Proficiency in Python and associated machine learning packages.
• Hands-on experience with OpenAI GPT and AWS SageMaker.
• Experience with Generative AI and Natural Language Processing (NLP) techniques.
• Knowledge of cloud computing and management systems, specifically Microsoft Azure.
• Experience with API and API Management.
• Ability to translate technical requirements from scientists and non-technical stakeholders.

Preferred Skills

• Prior experience in biotech or healthcare enterprise data science and IT environments.
• Experience with knowledge graphs (KPs) and neural networks.

Key Skills

Education

Bachelor's degree