Software Engineer

Periodic Labs

$120K — $160K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in building production systems like MES, LIMS, or ERP
  • Expertise in workflow/DAG orchestration
  • Proficient in data modeling for audit and provenance
  • Experience with concurrent systems involving resource locking and scheduling
  • Background in powder synthesis or materials manufacturing
  • Familiarity with scheduling algorithms for shared resources
  • Knowledge of event sourcing or append-only data architectures

Responsibilities

  • Build and scale Manufacturing Execution Systems (MES) for automated materials synthesis
  • Own scheduling, workflow, and data provenance systems
  • Develop workflow orchestration for multi-step synthesis pipelines
  • Implement instrument scheduling systems managing contention and priorities
  • Ensure complete lineage tracking for every sample action
  • Collaborate with the engineering lead to enhance lab automation platform
  • Work across tech stack including Python, React, and Kubernetes

Benefits

  • Ownership mentality fostering problem-solving without bureaucracy
  • Support for continuous learning of new scientific tools
  • Opportunity to contribute to novel scientific discoveries
  • Dynamic and rapidly growing workplace environment
  • Engagement with cutting-edge AI and physical sciences technologies
Full Job Description
About the Role

At Periodic Labs, our scientists don't just design experiments - they direct an automated materials synthesis lab that runs around the clock. Behind that lab is a system that has to work: scheduling dozens of instruments, tracking every sample from precursor to characterization, and orchestrating multi-step synthesis pipelines without dropping a single data point.

As our software engineer, you'll work with the engineering lead to build the orchestration systems that make all of this possible. You'll scale the scheduling, workflow, and data provenance systems that coordinate furnaces, dispensers, diffractometers, and more - turning scientific intent into fully attributable, reproducible outcomes at scale.

This is a senior, full-stack, production-grade role. You'll work across Python backends, React interfaces, and cloud infrastructure to ship systems that run reliably with minimal intervention. You'll work closely with our engineering lead and directly alongside scientists in the lab - understanding where things break, and building the systems that make them not break.

What You'll Do
  • Own and evolve the platform that orchestrates our automated synthesis lab - scheduling instruments, managing workflows, and tracking samples end-to-end
  • Build workflow orchestration for multi-step synthesis pipelines, including DAG execution, dependency resolution, and retry logic for long-running lab processes
  • Design and implement instrument scheduling systems that handle contention, prioritization, and batching across shared equipment with competing demands
  • Ensure complete data provenance - every sample, every action, every result is fully traceable with unambiguous lineage
  • Build the React interfaces that give scientists and lab operators visibility into experiment state, queue status, and system health
  • Work closely with infrastructure and lab engineering to keep systems reliable as we scale instrument count and experiment throughput
  • Identify bottlenecks in how science gets done and turn them into software before they become crises


You Will Thrive in This Role If You Have Experience With
  • Building production MES, LIMS, ERP, or process control systems where correctness is non-negotiable
  • Workflow and DAG orchestration - designing execution graphs that are robust, inspectable, and recoverable
  • Concurrent systems: resource locking, scheduling, and contention handling across shared infrastructure
  • Data modeling for audit and provenance use cases, including event sourcing or append-only architectures
  • Full-stack development across Python, React, and cloud-native infrastructure (Kubernetes a plus)
  • Scheduling algorithms for shared resources with hard and soft constraints
  • Working in or alongside physical lab, manufacturing, or materials environments


Especially Strong Candidates May Also Have
  • Direct experience in powder synthesis, ceramics, or materials manufacturing environments
  • Familiarity with laboratory instrumentation protocols and instrument communication standards
  • Experience with event sourcing or CQRS architectures at production scale

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