Conduct applied research on real healthcare data, focused on explainability, reinforcement learning, and long-context information retrieval
Design experiments, training models at scale, and collaborate with ML Ops and Product teams
Move quickly from concept to deployment
Code own experiments end-to-end

Requirements

PhD in computer science / informatics
At least 3 years of industry experience (will consider postdocs)
Experience designing novel architectures and pipelines in PyTorch/TensorFlow/JAX
Research expertise in interpretability, reinforcement learning, retrieval-augmented generation, or long-context information retrieval
Comfortable running large-scale training and evaluation on distributed infrastructure (e.g., Ray, FSDP, Lightning)
Track record publications at top ML venues (e.g., NeurIPS, ICML, EMNLP, MLHC, CHIL)

Benefits

Top-of-market compensation (salary + equity)
Flexible PTO
Hybrid in-office (min. 3 days per week)
Comprehensive health benefits
401(k) matching
Inspiring, brilliant, mission-driven teammates

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

applied researchexplainabilityreinforcement learninglong-context information retrievaldesigning architecturesPyTorchTensorFlowJAXlarge-scale trainingevaluation

Soft Skills

collaborationproblem-solvingcommunicationadaptabilitycreativity

Certifications

PhD in computer sciencePhD in informatics