About the role
About Periodic Labs The most important scientific discoveries of our time won’t happen in a traditional lab. We’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.
About
the Role As Periodic Labs scales the experimental engine behind our AI-driven materials discovery platform, we’re hiring a Process Engineer to own the end-to-end workflow of our powder synthesis lab. You’ll work directly across dispensing, mixing, pressing, reaction, recovery, and characterization — building the systems, controls, and instincts that keep a high-mix, fast-moving research process producing trustworthy data at increasing throughput. This is a hands-on, jack-of-all-trades role. You’ll move fluently between equipment troubleshooting, statistical process control, operator workflows, and the underlying science. The variation here is intentional — we run an enormous diversity of chemistries — and your job is to build the systems that absorb that intended variation while ruthlessly separating out the unintended kind. What you learn stabilizing the manual lab will directly shape how we design our automated, full-scale lab. What You’ll Do Own the powder synthesis workflow end-to-end — dispensing, mixing, pressing, reaction, recovery, and characterization — ensuring the process runs smoothly as throughput and complexity grow Map failure modes across the full process flow and design comprehensive systems and controls so failures either don’t happen or are caught and recovered quickly Apply statistical process control (SPC) and systems thinking to track key process inputs and outputs, identify drift, and bring processes into a stable, predictable state Troubleshoot and diagnose equipment issues across the lab — dispensing heads, reaction chambers, characterization tools — and drive root-cause investigations to durable fixes Investigate data integrity issues across the toolchain, including cases where equipment dispenses correctly but uploads data incorrectly, and partner with software and infra to adjust scripts and instrumentation Design operator-facing workflows that prevent sample mix-ups and reduce variation introduced by human handoffs Run design of experiments (DOE) to identify which recipe and process factors most impact outcomes, and use structured methodologies to converge efficiently Partner with research scientists, lab engineers, and software teams to translate the lessons from the manual lab into