Machine Learning Engineer, AI

Highlights

• Build systems connecting frontier AI models and lab capabilities to cure disease.
• Train biological foundation models on one of the largest AI clusters for biology.
• Build agentic systems linking frontier LLMs with biological foundation models.

What they offer

• Generous employer 401(k) match
• Paid time off to volunteer
• Funding for select family-forming benefits
• Relocation support

Ideal candidate

Experienced ML infrastructure builder who thrives at the intersection of AI and science and wants their systems work to directly unlock new discoveries and cures.

Requirements

• 5+ years building ML systems or distributed infrastructure at scale
• Strong Python, PyTorch and CUDA skills with understanding of model architectures, optimization and evaluation
• Experience with large-scale distributed systems, multi-GPU training, checkpointing and failure recovery
• Ability to diagnose performance problems across GPUs, memory, networking, storage and data loading
• Experience building large-scale data pipelines and shared research tools
• Experience deploying and monitoring models with version tracking, testing and CI
• Familiarity with containers and orchestration tools such as Slurm, Docker and Kubernetes