Research Engineer

About the Role

Make our models performant, fast, and reliable at scale by developing the core frameworks used to train and evaluate our ML models.

• Build datasets and algorithms to systematically evaluate and monitor model performance.
• Analyze model failure modes, working closely with researchers on experiments to mitigate them.
• Own the distributed training stack, removing runtime and reliability bottlenecks across all layers of the stack and architecture-parallelism, quantization, and kernel optimization and whatever else might move the needle.
• Own and contribute to our auto research and auto kernels frameworks.

Chai's models are moving beyond protein structure prediction into real-world therapeutic engineering. This is a chance to push the frontier of AI drug design, working alongside a rigorous and craft-obsessed team.

About You

Ideal backgrounds include deep industry experience working with top AI/ML teams on the kinds of problems we describe above-with strong software system design skills, proficiency in Python, and Pytorch or JAX fluency. We look for technical spikes where you have gone deep and demonstrated exceptional impact on real-world problems and systems.

We Offer

• The opportunity to work at the vanguard of AI research and frontier biology, with world-class people, on a mission that matters.
• We protect & promote a culture of high velocity and ownership.
• We compensate our team accordingly.