Principal Research AI Innovation Lead
Bristol Myers SquibbRemote - United States - US · Remote · full time · Principal
$145,020 – $175,728
Listed on Bristol Myers Squibb’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role leads the design and scaling of AI systems to accelerate pharmaceutical research, working across research, engineering, and data teams to build practical LLM-enabled solutions that help scientists make faster, better-informed decisions. It suits someone with deep expertise in both AI architecture and drug discovery or translational science who can evaluate whether AI outputs are scientifically sound and useful for real research.
Our summary, not Bristol Myers Squibb’s wording. The full posting is on their site.
Skills this role names
- Agentic Workflows
- Deep Learning
- Machine Learning
- Model Context Protocol
- Multi-Agent Systems
- Prompt Engineering
- Python
- Retrieval-Augmented Generation
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What they ask for
Required
- Bachelor's degree and 8+ years experience, or Master's degree and 6+ years experience, or PhD and 4+ years experience
- Hands-on experience designing and implementing AI systems, particularly agentic workflows and multi-agent orchestration
- Ability to assess whether AI-generated scientific outputs are scientifically grounded, appropriately caveated, and defensible
- Working knowledge of drug discovery, translational science, or related research domains
Nice to have
- Advanced degree (MS, PhD, PharmD) or equivalent in a scientific, computational, or AI field
- Direct experience in target identification, indication expansion, drug repurposing, biomarker discovery, translational research, or clinical evidence review
- Experience building AI systems that reason across heterogeneous biomedical data sources
- Experience designing AI evaluation frameworks and benchmark datasets for scientific quality
- Experience fine-tuning or developing biology-focused large language models or domain-specific AI systems
- Background in innovation labs, accelerators, startups, or rapid-prototyping environments