We are an AI + physical sciences lab building state of the art models to make novel scientific discoveries. We are well funded and growing rapidly. Team members are owners who identify and solve problems without boundaries or bureaucracy. We eagerly learn new tools and new science to push forward our mission.
About the RoleYou will build, and scale the Manufacturing Execution Systems (MES) that orchestrate our automated materials synthesis lab. You will own the scheduling, workflow, and data provenance systems that coordinate dozens of instruments—furnaces, dispensers, diffractometers, and more—to synthesize novel materials at scale. You will build workflow orchestration for multi-step synthesis pipelines and instrument scheduling systems that handle contention, priorities, and batching across shared equipment. You will ensure every sample action is fully attributable with complete lineage tracking. You will work across the stack—Python backend, React frontend, Kubernetes infrastructure—to build systems that run reliably in production with minimal intervention. You will work closely with the engineering lead to scale our lab automation platform as we grow instrument count and experiment throughput.
You might thrive in this role if you have experience with:Building production MES, LIMS, ERP, or process control systems with high correctness requirements
Workflow/DAG orchestration
Data modeling for audit and provenance use cases
Concurrent systems: resource locking, scheduling, contention handling
Powder synthesis, ceramics, or materials manufacturing environments
Scheduling algorithms for shared resources with constraints
Event sourcing or append-only data architectures
Top Skills
What We Do
We're building AI scientists and the autonomous laboratories for them to operate.
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