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MES Engineer Automated Materials Lab

Job in Menlo Park, San Mateo County, California, 94029, USA
Listing for: Periodic Labs
Full Time position
Listed on 2026-10-17
Job specializations:
  • Software Development
    Software Engineer
Salary/Wage Range or Industry Benchmark: 150000 - 230000 USD Yearly USD 150000.00 230000.00 YEAR
Job Description & How to Apply Below

Location

Menlo Park

Employment Type

Full time

Location Type

On-site

Department

Atoms:
Lab, physics, chemistry, etc.

About Periodic Labs

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 Role

You 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  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

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