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Periodic Labs

AI-driven materials discovery and design

Automation Engineer

Controls & Automation EngineeringConfirmed live in the last 24 hours
Full-timeMenlo Park, CA, USAIn-person

About the Job

Requirements

  • A Bachelor of Science in Electrical Engineering, Computer Science, Mechanical Engineering, or Controls, or equivalent.
  • At least 5 years of experience in lab automation, integration, or industrial automation software.
  • Hands-on experience with robotic lab automation systems.
  • Strong scripting or programming experience; Python is preferred.
  • Familiarity with APIs, databases, and enterprise software integration.
  • Hands-on experience with information management and execution systems such as LIMS or MES.
  • A bachelor's degree or similar experience is the minimum education requirement.

Responsibilities

  • Collaborate with bench scientists to translate experiments and lab workflows into clear integration specifications and data models.
  • Work with integrators to design and build automated workcells for materials research and development.
  • Build and maintain services that connect instruments and robots to lab information systems.
  • Develop instrument drivers that automate lab workflows by generating command sequences and invoking vendor API or SDK methods.
  • Collaborate with AI and data scientists to integrate the autonomous lab with AI models for experiment analysis and planning.

Desired Qualifications

  • Experience with containers, continuous integration and continuous delivery (CI/CD), and Git-based workflows.
  • Background in lab informatics or scientific data management.

About the Company

Periodic Labs

AI-driven materials discovery and design

Periodic Labs uses artificial intelligence to model, predict, analyze, and design new materials. Its platform learns from large scientific datasets to suggest viable material compositions, structures, and processing methods that meet performance targets. The team combines AI expertise from OpenAI and DeepMind, applying it specifically to materials science to offer data-driven material design for energy, electronics, and manufacturing. The company aims to accelerate materials discovery, enabling clean energy, better semiconductors, and stronger supply chains by reducing the time and cost of traditional research.

Company size
51-200
Company stage
Seed
Total funding
$300M
Headquarters
Menlo Park, CA
Founded
2025

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