---
title: 'ML Systems Engineer at Periodic Labs'
canonical: 'https://feeny.ai/job/ml-systems-engineer-periodic-labs-menlo-park-d8fx36fbd5em'
type: 'job'
last_seen: '2026-09-07'
---

# ML Systems Engineer at Periodic Labs

- **Company:** Periodic Labs
- **Location:** Menlo Park, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-04-29
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.ashbyhq.com/periodic-labs/d9180228-c113-4d5f-a4d6-793994e50b7c

## Job description

## ABOUT PERIODIC LABS

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

You’ll work alongside some of the world’s leading ML systems engineers, including leaders behind Megatron-LM, SGLang, Liger Kernel, TorchRec, CleanRL, TorchRL, and JAX-MD.

We’re looking for exceptional ML Systems Engineers to build the agentic infrastructure powering our large-scale training, inference, and reinforcement learning. You’ll own critical pieces of the ML systems stack to maximize performance, scalability, reliability, and productivity for both engineers and AI agents.

## WHAT YOU'LL DO

- Build and optimize large-scale training and reinforcement learning infrastructure while ensuring its correctness
- Develop high-performance inference and serving systems
- Design distributed runtimes and scheduling systems for complex ML workloads
- Build secure and large-scale sandboxing and execution environments
- Optimize memory, GPU kernels and communication for maximum throughput and end-to-end efficiency
- Improve scalability, reliability, and efficiency across the ML systems stack

## WHAT WE'RE LOOKING FOR

- Strong systems programming and performance engineering skills
- Experience building high-performance ML infrastructure at scale
- Ability to own complex technical problems end-to-end
- Strong coding ability and engineering judgment, including the ability to work effectively with AI agents to design, implement, test, and debug complex systems
- High ownership, fast execution, and a passion for pushing the frontier of AI systems and accelerating scientific discovery

YOU SHOULD HAVE DEEP EXPERTISE IN AT LEAST ONE OF THE FOLLOWING:

- Training: Strong experience building, debugging and optimizing large-scale training systems with Megatron-LM. Familiarity with TorchTitan, FSDP, veRL, Slime, or other distributed training systems is a plus.
- Distributed Runtime: Strong experience with Ray. Familiarity with Monarch or other distributed execution frameworks is a plus.
- Inference: Strong experience with SGLang. Familiarity with vLLM, TensorRT-LLM, or production LLM serving systems is a plus.
- Sandboxing: Strong experience with secure execution environments, containers, virtualization, or code sandboxing.
- GPU Kernels: Strong experience with CUDA, Triton, CUTLASS, CuTe, or custom GPU kernel development.
- GPU Communication: Strong experience with NCCL, NVLink, InfiniBand, RDMA, GPUDirect RDMA, or large-scale communication optimization.

## MECHANICS

Minimum education: Bachelor’s degree or similar experience

Location: Menlo Park, CA (Soon: San Francisco, too)

Compensation: $250,000-$350,000 base + equity

Visa sponsorship: Yes, we sponsor visas.

We’re building a team of the world’s best — the scientists, engineers, and problem-solvers who don’t just follow the frontier, they define it. If you’re driven to bring AI to life in the physical world and make discoveries that have never been made before, you belong here.

## About Periodic Labs

## Company Overview
- **One-liner**: Periodic Labs is building AI scientists and autonomous laboratories to accelerate scientific discovery in the physical sciences, starting with materials design and semiconductor research.
- **Entity Type**: Private (seed-stage, $300M total funding raised in 2025)
- **Headquarters**: San Francisco, California, USA (primary) and Menlo Park, California, USA (dual locations) [cbinsights.com](https://www.cbinsights.com/company/periodic-labs), [linkedin.com](https://www.linkedin.com/company/periodic-labs)
- **Founded**: 2025 [cbinsights.com](https://www.cbinsights.com/company/periodic-labs)
- **Founders**: Ekin Dogus Cubuk (Co-Founder) and other undisclosed founding team members with backgrounds at OpenAI, DeepMind, and Google [linkedin.com](https://www.linkedin.com/company/periodic-labs), [periodic.com](https://periodic.com/)

## Core Business
- **Primary industry/industries**: Physical sciences R&D, artificial intelligence, autonomous laboratory systems
- **Target customers**: B2B – enterprises in semiconductor manufacturing, materials science, energy, and other deep-tech sectors requiring experimental research
- **Mission or purpose statement**: “Our goal is to create an AI scientist” that can autonomously hypothesize, run experiments, and learn from results to discover new materials and accelerate technological progress [periodic.com](https://periodic.com/)

## Products & Services
- **AI Scientist**: A suite of AI models trained to generate hypotheses, design experiments, and interpret results across physical science domains.
- **Autonomous Laboratories**: Fully automated, high-throughput experimental platforms that produce large volumes of high-quality data (including negative results) to train AI models. [periodic.com](https://periodic.com/)
- **Custom Agents for Industry**: Tailored AI agents for engineers and researchers, e.g., helping a semiconductor manufacturer analyze heat dissipation data to accelerate iteration. [periodic.com](https://periodic.com/)

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private seed-stage company)
- **Key Metric**: Total funding raised – $300M in a single seed round (2025) [cbinsights.com](https://www.cbinsights.com/company/periodic-labs)
- **Notable Investors/Partners**: a16z, Felicis, DST, NVentures (NVIDIA’s venture arm), Accel, Emerson Collective, Fellows Fund, Coatue; individual backers include Jeff Bezos, Elad Gil, Eric Schmidt, Jeff Dean. Also collaborating with academic advisors from Stanford, Northwestern, and more. [periodic.com](https://periodic.com/), [cbinsights.com](https://www.cbinsights.com/company/periodic-labs)
- **Growth Signals**: 40 employees as of mid-2026, with monthly headcount growth of +19.6% and 25 active job postings (+47.1% quarterly growth) [linkedin.com](https://www.linkedin.com/company/periodic-labs)

## Competitive Advantages
- **Proprietary data generation**: Autonomous labs produce massive, unique datasets (including valuable negative results) that do not exist in public literature, creating a data moat.
- **Founding team pedigree**: Core team co-created ChatGPT, DeepMind’s GNoME, OpenAI’s Operator (Agent), MatterGen, and scaled autonomous physics labs – rare concentration of AI + science talent. [periodic.com](https://periodic.com/)
- **End-to-end integration**: AI models, simulation, and physical experimentation are all in-house, enabling rapid closed-loop learning.

## Strategic Focus
- **Scale autonomous labs**: Expand capacity to generate experimental data across multiple physical science domains.
- **Target high-impact problems**: Superconductor discovery, semiconductor heat dissipation, and other materials challenges that can unlock Moore’s Law, advanced energy grids, and space travel. [periodic.com](https://periodic.com/)
- **Develop the first generation of AI scientists**: Train models that can operate independently of human input across the entire scientific method.

## Why Work Here
- **Culture**: “From bits to atoms” – a deep-tech startup blending frontier AI with hands-on lab work. Emphasis on rapid iteration and real-world impact.
- **Work policy**: In-office preferred; primary offices in Menlo Park and San Francisco, CA. Most roles are on-site. [builtin.com](https://builtin.com/company/periodic-labs)
- **Notable perks**: Work alongside world-class AI researchers and experimental scientists; access to cutting-edge automated lab equipment; early-stage equity and high-growth trajectory.
- **Engineering culture**: 34% of employees are in technical roles; talent sourced from OpenAI, Google DeepMind, Meta, xAI, and Stanford – strong peer learning environment. [linkedin.com](https://www.linkedin.com/company/periodic-labs)

## Sources
1. [periodic.com](https://periodic.com/)
2. [builtin.com](https://builtin.com/company/periodic-labs)
3. [cbinsights.com](https://www.cbinsights.com/company/periodic-labs)
4. [linkedin.com](https://www.linkedin.com/company/periodic-labs)
5. [jobs.ashbyhq.com/periodic-labs](https://jobs.ashbyhq.com/periodic-labs)

## Other roles at Periodic Labs

- [Computational Scientist, Differentiable Physics](https://feeny.ai/job/computational-scientist-differentiable-physics-periodic-labs-menlo-park-0y6vkjnce8d0) — Menlo Park, CA
- [Research Scientist/Research Engineer, Materials](https://feeny.ai/job/research-scientist-research-engineer-materials-periodic-labs-menlo-park-gx5csg53tr95) — Menlo Park, CA
- [Technical Recruiter](https://feeny.ai/job/technical-recruiter-periodic-labs-menlo-park-04dyj1a17h1w) — Menlo Park, CA
- [Business Operations, Product & Science](https://feeny.ai/job/business-operations-product-science-periodic-labs-menlo-park-bqebn8py4dnh) — Menlo Park, CA
- [Process Technician, Thin Films](https://feeny.ai/job/process-technician-thin-films-periodic-labs-menlo-park-v0m9kw9t9506) — Menlo Park, CA
- [Research Engineer, Lab Automation](https://feeny.ai/job/research-engineer-lab-automation-periodic-labs-menlo-park-x22bb9y5rh0q) — Menlo Park, CA
- [Research Engineer, Midtraining](https://feeny.ai/job/research-engineer-midtraining-periodic-labs-menlo-park-0xmve48my4pp) — Menlo Park, CA
- [Mechanical Engineer](https://feeny.ai/job/mechanical-engineer-periodic-labs-menlo-park-4rk1qv8jx0ps) — Menlo Park, CA
- [Research Engineer, Semiconductor](https://feeny.ai/job/research-engineer-semiconductor-periodic-labs-menlo-park-7pcqbzy21h6n) — Menlo Park, CA
- [Instrumentation & Controls  (Technician/Electrician)](https://feeny.ai/job/instrumentation-controls-technician-electrician-periodic-labs-menlo-park-4k691hbr206e) — Menlo Park, CA