---
title: 'Forward Deployed Engineer, Quantum Simulations at Periodic Labs'
canonical: 'https://feeny.ai/job/forward-deployed-engineer-quantum-simulations-periodic-labs-menlo-park-rdc68h8gwvqs'
type: 'job'
last_seen: '2026-09-07'
---

# Forward Deployed Engineer, Quantum Simulations at Periodic Labs

- **Company:** Periodic Labs
- **Location:** Menlo Park, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-06-16
- **Last confirmed live:** 2026-09-07
- **Apply:** https://jobs.ashbyhq.com/periodic-labs/a059aee9-881a-42f2-b9d6-6685b133545f

## 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

Periodic Labs is building AI systems that reason over quantum mechanical simulations to accelerate materials discovery — and we need engineers who can take that capability directly into the hands of the scientists and organizations who need it most. As a Forward Deployed Engineer focused on quantum simulations, you will embed with customers and research partners to understand their simulation workflows, translate their scientific needs into working solutions, and close the gap between what our platform can do and what the world's best materials scientists require.

This is a technical and scientific role, not a pure account management role. You will write code, debug workflows, configure integrations, and surface product gaps back to our internal teams. You will be the person in the room who understands both the physics of a density functional theory calculation and the API call needed to run it at scale. You will work directly with customers ranging from advanced semiconductor manufacturers to national labs to energy companies — and your work will directly shape how Periodic Labs grows into these markets.

## WHAT YOU'LL DO

- Embed with customers and research partners to understand their quantum simulation workflows — DFT, quantum chemistry, many-body perturbation theory, mesoscopic scale modeling or force-field-based methods — and translate those workflows into solutions built on Periodic Labs infrastructure
- Write and maintain integration code, custom scripts, and workflow automation that connect customer simulation environments (VASP, Quantum ESPRESSO, FHI-aims, CP2K, or similar) to Periodic Labs systems
- Configure, validate, and troubleshoot high-throughput simulation pipelines on cloud and HPC environments, ensuring accuracy, reproducibility, and performance
- Serve as the primary technical contact for a portfolio of customers, owning the relationship from initial deployment through steady-state operation and expansion
- Surface detailed product feedback — missing capabilities, integration friction, accuracy gaps — to Periodic Labs research and engineering teams and help prioritize the roadmap
- Collaborate with internal ML and materials science teams to test new simulation capabilities against customer use cases before release
- Develop reusable technical assets: onboarding guides, workflow templates, integration libraries, and best-practice documentation that accelerate future deployments
- Represent Periodic Labs at technical conferences, workshops, and customer sites — communicating our simulation capabilities credibly to expert scientific audiences

YOU WILL THRIVE IN THIS ROLE IF YOU HAVE

- 3–7 years of experience working with quantum chemistry or condensed matter simulation codes, either in research or in an applied/industry context
- Hands-on experience with at least one major ab initio or DFT code (VASP, Quantum ESPRESSO, FHI-aims, CP2K, GPAW, or equivalent)
- Strong programming skills in Python; comfortable scripting automation, parsing simulation outputs, and building lightweight tooling around simulation workflows
- Experience running and managing calculations on HPC clusters or cloud compute environments (AWS, GCP, Azure), including job schedulers such as SLURM or PBS
- Ability to communicate complex simulation concepts clearly to both technical and semi-technical audiences — you can explain exchange-correlation functionals to a physicist and convergence testing to a program manager
- A customer-facing or deployment-facing mindset: you take ownership of outcomes, communicate proactively, and don't wait to be told when something is broken
- Comfort operating in ambiguous, fast-moving environments where the product, the science, and the customer need are all evolving simultaneously

## ESPECIALLY STRONG CANDIDATES MAY ALSO HAVE

- Experience with Machine learned interatomic potentials (MLIPs) like MACE or UMA and differentiable MD simulation packages.
- Experience with materials databases and frameworks (e.g., the Materials Project, OQMD, AiiDA, or Atomate2 workflow frameworks)
- Familiarity with the Periodic Labs Onnes platform or similar AI-assisted experimental design systems
- Domain depth in a specific application area relevant to Periodic Labs customers: advanced semiconductor packaging, thin-film deposition, superconducting materials, or energy storage
- Prior experience in a forward deployed, solutions engineering, or field CTO role at a deep tech or scientific software company

## MECHANICS

Minimum education: Bachelor’s degree or similar experience

Location: Menlo Park, CA or Montreal, Canada. (Soon: San Francisco, too)

Compensation: The annual compensation range for this role - $200,000-$275,000

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)

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