Senior Manager, Intelligence Systems Lab
Bristol Myers Squibb
2 months ago
Remote friendly (Seattle, WA)
United States
IT
Responsibilities:
- Research and develop AI agent frameworks for reasoning, planning, memory, and generalization (including abstraction, goal decomposition, adaptive planning).
- Design and run benchmarking/evaluation experiments; create evaluation methodologies, test harnesses, datasets, and measurement frameworks; apply rigorous experimental design and statistical analysis.
- Engineer agentic AI solutions: build multi-agent systems (e.g., Strands, LangGraph, DSPy), develop RAG/knowledge graph/conversational AI applications, and implement autonomous workflows.
- Rapidly prototype and document proof-of-concepts and technical methodologies.
- Collaborate cross-functionally with analytics and business stakeholders (Commercial, GPS/Manufacturing, Clinical Development, Research) and translate research into business language.
- Mentor teammates and contribute to evaluation/benchmarking best practices and knowledge sharing.
Qualifications:
- BA/BS required in a quantitative field (Computer Science/Data Science/Statistics/Math/Cognitive Science/Engineering); MS preferred.
- 3+ years hands-on experience in data science, machine learning, AI development, or AI research (pharma/life sciences preferred).
- Python proficiency; ML frameworks (Scikit-Learn, TensorFlow, PyTorch); agentic frameworks (Strands, LangGraph, AutoGen, DSPy, CrewAI); LLMs/prompt engineering/RAG; benchmarking & evaluation familiarity.
- SQL; cloud (AWS/Azure/GCP); Git/version control; experimental design & statistical analysis (preferred).
Benefits (explicit):
- Health coverage (medical/pharmacy/dental/vision); wellbeing programs; 401(k), disability, life/accident insurance, supplemental health; Paid Time Off (flexible time off/annual vacation and holidays as described).
Compensation (explicit):
- $133,710–$178,221 depending on location.
- Research and develop AI agent frameworks for reasoning, planning, memory, and generalization (including abstraction, goal decomposition, adaptive planning).
- Design and run benchmarking/evaluation experiments; create evaluation methodologies, test harnesses, datasets, and measurement frameworks; apply rigorous experimental design and statistical analysis.
- Engineer agentic AI solutions: build multi-agent systems (e.g., Strands, LangGraph, DSPy), develop RAG/knowledge graph/conversational AI applications, and implement autonomous workflows.
- Rapidly prototype and document proof-of-concepts and technical methodologies.
- Collaborate cross-functionally with analytics and business stakeholders (Commercial, GPS/Manufacturing, Clinical Development, Research) and translate research into business language.
- Mentor teammates and contribute to evaluation/benchmarking best practices and knowledge sharing.
Qualifications:
- BA/BS required in a quantitative field (Computer Science/Data Science/Statistics/Math/Cognitive Science/Engineering); MS preferred.
- 3+ years hands-on experience in data science, machine learning, AI development, or AI research (pharma/life sciences preferred).
- Python proficiency; ML frameworks (Scikit-Learn, TensorFlow, PyTorch); agentic frameworks (Strands, LangGraph, AutoGen, DSPy, CrewAI); LLMs/prompt engineering/RAG; benchmarking & evaluation familiarity.
- SQL; cloud (AWS/Azure/GCP); Git/version control; experimental design & statistical analysis (preferred).
Benefits (explicit):
- Health coverage (medical/pharmacy/dental/vision); wellbeing programs; 401(k), disability, life/accident insurance, supplemental health; Paid Time Off (flexible time off/annual vacation and holidays as described).
Compensation (explicit):
- $133,710–$178,221 depending on location.