Senior Manager, Intelligence Systems Lab
Bristol Myers Squibb
2 months ago
Remote friendly (Princeton, NJ)
United States
IT
Description: Senior Manager, Intelligence Systems Lab. Conduct research and develop agentic AI systems using rigorous evaluation science; implement reasoning, planning, memory, and generalization capabilities and benchmarking methodologies. Support cross-functional stakeholders across Commercial, Manufacturing, Clinical Development, and Research.
Key Responsibilities:
- Research and framework development for AI agent reasoning/planning/memory/generalization; build cognition frameworks (abstraction, goal decomposition, adaptive planning).
- Design and run benchmarking/evaluation experiments; create evaluation methodologies, test harnesses/datasets, measurement frameworks; apply experimental design and statistical analysis.
- Hands-on agentic AI development: build multi-agent systems (e.g., Strands, LangGraph, DSPy); develop RAG apps, knowledge graphs, conversational AI; implement autonomous workflows.
- Rapid prototyping and innovation; develop proof-of-concepts; translate research into production-ready capabilities; document results.
- Cross-functional collaboration and mentorship/best practices in evaluation/benchmarking and guidance to junior team members.
Qualifications/Skills (required unless noted):
- BA/BS in a quantitative field; MS preferred.
- Python; ML frameworks (Scikit-Learn/TensorFlow/PyTorch); agentic frameworks (Strands/LangGraph/AutoGen/DSPy/CrewAI, etc.); LLMs, prompt engineering, RAG.
- SQL; cloud (AWS/Azure/GCP); Git.
- 3+ years hands-on data science/ML/AI development or research.
Benefits (explicitly stated): health coverage; wellbeing support (EAP etc.); 401(k) and insurance/disability; paid time off (incl. flexible time off or vacation depending on role/location).
Key Responsibilities:
- Research and framework development for AI agent reasoning/planning/memory/generalization; build cognition frameworks (abstraction, goal decomposition, adaptive planning).
- Design and run benchmarking/evaluation experiments; create evaluation methodologies, test harnesses/datasets, measurement frameworks; apply experimental design and statistical analysis.
- Hands-on agentic AI development: build multi-agent systems (e.g., Strands, LangGraph, DSPy); develop RAG apps, knowledge graphs, conversational AI; implement autonomous workflows.
- Rapid prototyping and innovation; develop proof-of-concepts; translate research into production-ready capabilities; document results.
- Cross-functional collaboration and mentorship/best practices in evaluation/benchmarking and guidance to junior team members.
Qualifications/Skills (required unless noted):
- BA/BS in a quantitative field; MS preferred.
- Python; ML frameworks (Scikit-Learn/TensorFlow/PyTorch); agentic frameworks (Strands/LangGraph/AutoGen/DSPy/CrewAI, etc.); LLMs, prompt engineering, RAG.
- SQL; cloud (AWS/Azure/GCP); Git.
- 3+ years hands-on data science/ML/AI development or research.
Benefits (explicitly stated): health coverage; wellbeing support (EAP etc.); 401(k) and insurance/disability; paid time off (incl. flexible time off or vacation depending on role/location).