Senior Research Engineer, ML Lead, Health Frontiers

Overview

In this role, you will lead end-to-end ML experimentation to advance health-focused AI systems. You’ll collaborate with scientists to translate research questions into measurable endpoints, design and evaluate models, and guide technical architecture and mentorship. You’ll own the experimentation loop, build scalable data pipelines, and drive production-ready improvements. The role combines frontier research with practical deployment to improve health outcomes at scale.

Responsibilities

• Design, train, and evaluate ML models across the experimentation loop
• Develop autoresearch agents to accelerate research workflows and discovery
• Create evaluation frameworks for scientific reasoning, calibration, and real-world utility
• Collaborate with scientists to translate research questions into endpoints and experimental designs
• Provide technical leadership through architecture reviews and mentoring
• Lead technical agendas and make decisive decisions to overcome obstacles
• Transform research into scalable production systems

Key requirements

• Bachelor’s degree or equivalent practical experience
• 5 years of experience in ML research or research engineering with leadership of technical projects
• 3 years of experience with training/evaluating large-scale foundation models and data pipelines for heterogeneous datasets
• 3 years of experience with modern ML frameworks (JAX, PyTorch, TensorFlow) and distributed training on accelerators
• 3 years of experience designing evaluations, metrics, and ablations for research projects

• leadership
• collaboration
• strategic thinking
• JAX
• PyTorch
• TensorFlow

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