Overview
develop agentic ai systems using rigorous evaluation science; implement reasoning, planning, memory, and generalization capabilities; build benchmarking methodologies to assess agent performance. Support cross-functional stakeholders in commercial, manufacturing, clinical development, and research.
responsibilities
* research reasoning/planning/memory/generalization architectures for ai and multi‑agent systems; build cognition frameworks (abstraction, goal decomposition, adaptive planning).
* design and run benchmarking/evaluation experiments; create evaluation datasets, test harnesses, and measurement frameworks; apply experimental design and statistical analysis.
* engineer and deploy agentic solutions: multi‑agent systems (e.g., strands, langgraph, dspy), rag applications, knowledge graphs, conversational ai, and autonomous workflows.
* rapid prototype and translate research into production‑ready capabilities; document research and technical methods.
* collaborate cross‑functionally; translate ai research into business language; mentor and support best practices in evaluation and research methodology.
qualifications
* ba/bs required (quantitative: cs, data science, statistics, math, cognitive science, or engineering). Ms preferred.
* 3+ years hands‑on experience in data science/ml/ai development or research; pharma/life sciences preferred.
* python; ml frameworks (scikit‑learn, tensorflow, pytorch); agentic frameworks (strands, langgraph, autogen, dspy, crewai); llms/prompting/rag; benchmarking & evaluation methods.
* sql; cloud (aws/azure/gcp); git; experimental design/statistical analysis preferred.
benefits
* health coverage; wellbeing support; 401(k) and protection benefits; paid time off (including flexible time off and/or vacation depending on location).
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