Software Engineer, Inference & Platform

About Chai Discovery

Chai is a research lab working on AI to unlock biology. Our models design new molecules for new medicines. We are changing how biologists develop drugs, just as language models are changing how engineers write code. Our vision is a design suite for molecules, with applications across life sciences, agriculture, materials and beyond.

Our founders have been at the forefront of this field from the beginning. We are backed by Thrive, General Catalyst, OpenAI, Dimension and other tier-one investors. We partner with global life sciences companies like Eli Lilly on deals that are transforming industry.

We are known for talent density, rigorous research and pace of execution.

About the role

Inference and platform engineers make Chai's models fast, cheap, and reliable at scale, and build the platform that serves the design suite for molecules. You'll own the serving stack that turns our frontier models into a product scientists depend on: latency, throughput, GPU efficiency, batching, and autoscaling across a large multi-cloud GPU fleet.

That same platform underpins our product surface, our evaluation suite, and our partner deployments, so the work sits directly on the critical path of the business. This is deep systems work, and we hold the infrastructure to the same craft bar as the models it serves.

Our models have moved beyond structure prediction into real therapeutic engineering, and the platform has to scale with a business that's moving fast and with model architectures that keep changing under you.

You've built high-performance services that developers love, moved ML systems into production at scale, and can see around the corners before they become outages. You'll work closely with the researchers who train the models, the product engineers who build on them, and the commercial team deploying them to the world's largest pharma companies, alongside a craft-obsessed team of micro-pessimists and macro-optimists.

About you

We index on systems judgment, ownership, and the scars that come from having run production infrastructure before. We're looking for engineers who get obsessed with hard problems and don't give up easily. We look for:

• 5+ years building production systems, with real depth in performance, distributed systems, or ML serving

• Experience optimizing model inference: GPU utilization, batching, quantization, caching, or kernel-level work

• End-to-end ownership of 24/7 systems, including observability, alerting, and incident response

• Experience across both 0-to-1 buildouts and 1-to-n scale-ups, with an always-evolving playbook you bring wherever you go

• The instinct to treat cost and efficiency as first-class constraints, not afterthoughts

A background in biology is not required. What makes the difference is technical excellence, curiosity about the domain, and grit.

We offer

The opportunity to work at the leading edge of AI research, with world-class people, on a mission that matters. We protect & promote a culture of high velocity and ownership. We offer highly competitive compensation.