Research Engineer, ML Infrastructure

present of AI; San Francisco (CA); Sur place; USD 180 000 - 250 000; Plein temps

Résumé du poste

Chai Discovery in San Francisco is seeking a Senior AI/Data engineer to make large model training fast, stable, and cost efficient. You will work on training code from full models down to GPU kernels, keeping long runs healthy on large GPU clusters.

A strong candidate has distributed training experience, performance profiling, and reliability work such as checkpointing and recovery, plus solid Python and PyTorch or JAX skills.

Qualifications

• Hands-on experience with distributed training across multi-GPU clusters.
• Proficiency in performance profiling and throughput optimization.
• Reliability work including checkpointing and recovery.
• Strong Python and PyTorch or JAX skills.

Responsabilités

• Work on training code from full models down to GPU kernels.
• Make large model training fast, stable and cost efficient.
• Collaborate with researchers to scale runs and test new architectures.
• Ensure long runs on big GPU clusters stay healthy with fault tolerance.

Connaissances

Distributed training

Performance profiling

Checkpointing and recovery

Python

PyTorch

JAX

Description du poste

AI & Data · San Francisco office · FullTime · Senior level

The role is about making large model training fast, stable and cost efficient. That means working on the training code from whole models down to individual GPU kernels, and keeping long runs on big GPU clusters healthy. A strong candidate has deep hands-on experience with distributed training, performance profiling, and reliability work such as checkpointing and recovery, plus solid Python and PyTorch or JAX skills.

How it fits the AI era

AI is the product here, so the work is about building the machinery that lets new model ideas be tested and scaled quickly. Tools that help write and tune code can speed up routine tasks, but deciding where a training run is losing time, and how to make it dependable, still takes careful human judgment. Working closely with researchers to turn new architectures into runs that scale stays a people-centered job.

How it builds AI experience

The role gives direct experience training frontier models on biochemical structure and interaction, which is a specialized area within AI for drug discovery. Someone can build toward it by practicing multi-GPU training of open protein or molecule models, profiling them, and fixing throughput and failure problems. Learning the basics of how these models are used by drug scientists helps connect the infrastructure work to real outcomes.

Worth showing

• Distributed training at scale
• GPU profiling and optimization
• Fault tolerant training systems
• PyTorch or JAX depth

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About Chai Discovery

Frontier AI foundation models and computer-aided design suite to predict and reprogram biochemical molecules, per the company.