Senior Research Engineer, ML Systems
Core
Building frontier AI models and the underlying technology, systems, and infrastructure to power large-scale biological research and therapeutic development.
Role type
Senior Research Engineer (ML Systems)
Builds
Frontier AI models, distributed training pipelines, experiment frameworks, and tooling for biological data research.
Domain
Life Sciences / AI / Large-scale Deep Learning
Deliverable
production ML models | infrastructure
Required skills
Large-scale experiment design and execution, distributed training frameworks, GPU/accelerator optimization, CUDA kernel development, XLA, data pipeline engineering, reproducible research tooling, open-source ML framework contributions, quantitative intuition for system design.
Preferred skills
Background in mathematics or physics, experience with biological data (genomic sequences, protein structures, molecular data), familiarity with Kubernetes or Dagster, publications at major ML venues.
Technologies
PyTorch, JAX, MLX, CUDA, XLA, Kubernetes, Dagster
Responsibilities
Design and implement custom architectures for novel data modalities, optimize training runs to push hardware limits, build robust and flexible tooling for a small team operating at scale, collaborate with researchers in genomics and computational biology, ensure research reproducibility and reliability.
Seniority
Senior, hands-on IC