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Periodic Labs

Product Engineer

Menlo Park$250k–$350kfulltimemidAdded 1 month ago

About this role

Periodic Labs seeks a Product Engineer to build the software interface between AI models and materials scientists, creating agentic systems that help researchers plan experiments, analyze data, and make decisions. You'll own products end-to-end—from interfaces to backend systems—working closely with scientists and model researchers to turn cutting-edge AI into practical scientific workflows.

What you'll do

  • Design and prototype agentic products including copilots, experiment planning systems, and workflow automation tools
  • Build interfaces and interaction patterns for scientists to collaborate with and supervise AI agents
  • Integrate lab systems, scientific data, and frontier models into cohesive product experiences
  • Work with model researchers to establish feedback loops, telemetry, and evaluation signals
  • Spend time with scientists to identify bottlenecks and turn them into products
  • Own full-stack delivery from data models and APIs to deployment and observability

What they're looking for

  • Full-stack product engineering (backend, APIs, frontend)
  • Agentic AI and LLM application design
  • Systems integration and workflow orchestration
  • Rapid prototyping and iteration
  • Scientific domain understanding or ability to learn quickly
  • Product thinking and user-centered design
  • Python or similar languages
  • Observability and telemetry implementation

Benefits

  • $250,000-$350,000 base salary plus equity
  • Visa sponsorship available
  • Opportunity to define product engineering culture at an early-stage company
  • Work with frontier AI models in materials science
  • Direct collaboration with world-class scientists and researchers
  • Located in Menlo Park with expansion to San Francisco
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Periodic Labs

Periodic Labs builds AI systems and autonomous lab infrastructure to accelerate materials discovery and scientific research, integrating machine learning with physical lab workflows and quantum simulation. The company is hiring for infrastructure engineers, product engineers, research engineers, and deployment specialists who bridge AI models with materials scientists and lab automation systems.

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Likely interview questions

  • Tell us about a time you shipped a product feature quickly while maintaining quality. How did you balance speed with the need to get feedback from end users?
  • Describe your experience building interfaces or systems on top of AI models or agents. What were the key challenges in translating model capabilities into user-facing products?
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