From bits to atoms. Backed by Accel, Lightspeed and a16z.
About the role
We’re hiring software engineers to build the backend and distributed systems that form the software backbone of an AI-native physical science lab. These systems turn scientific intent into reliable execution: scheduling large simulation workloads, orchestrating experiments and shared equipment, and connecting instruments and automation to the rest of our software.
What they're looking for
- Strong software engineering fundamentals and a track record of building production backend or distributed systems
- Experience with asynchronous or long-running work, such as batch jobs, workflow orchestration, data pipelines, schedulers, or shared-resource systems
- The ability to reason clearly about concurrency, idempotency, partial failures, consistency, and resource contention
- Experience designing maintainable APIs and data models for complex systems
- Strong debugging skills across services, infrastructure, dependencies, and data
- Comfort working with technical collaborators to turn ambiguous needs into reliable systems
More about this role
We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
We’re hiring software engineers to build the backend and distributed systems that form the software backbone of an AI-native physical science lab. These systems turn scientific intent into reliable execution: scheduling large simulation workloads, orchestrating experiments and shared equipment, and connecting instruments and automation to the rest of our software.
Depending on your background and interests, you may work across simulation infrastructure, lab orchestration, or automation systems. You do not need prior experience in every area. We care most about strong engineers who can reason about complex systems, make failure visible, and build software that remains reliable as scientific work scales.
You’ll work directly with scientists, infrastructure engineers, and lab engineers to understand how research gets...
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