Join a global healthcare biopharma company with a 130-year legacy, driven by digital technology and data-backed approaches
Job Summary
Join a global healthcare biopharma company with a 130-year legacy, driven by digital technology and data-backed approaches.
Redefine the "art of the possible" by developing and testing GenAI software solutions and integrating them with R&D enterprise applications.
Own end-to-end model integration, data engineering, and application development, mentor engineers and data scientists, and help define architecture, ML Ops practices, and governance for secure, scalable AI solutions in a regulated environment.
Matching Summary
Join a global healthcare biopharma company with a 130-year legacy, driven by digital technology and data-backed approaches.
Skills & Requirements
Must-have
Generative AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Prompt Engineering
Python
Machine Learning
Data Pipelines
MLOps
Backend Development
APIs
Microservices
Nice-to-have
Regulatory Document Systems
GxP Compliance
Data Governance
Secure Data Handling
Prompt Evaluation
Red-Team Testing
Model Explainability
Life Sciences
Pharma Domain
Key Requirements
7+ years software engineering experience
Hands-on experience in AI/ML systems and data engineering
Strong experience with generative AI technologies
Proficiency with Python and ML frameworks
Experience building data pipelines
Experience with vector databases and semantic search
Familiarity with model serving and ML Ops tools
Strong backend development skills
Experience with cloud platforms (AWS preferred)
Solid understanding of data governance, privacy, and secure handling