Forward Deployed Engineer, Physics & Simulation

Periodic Labs; Menlo Park (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

Periodic Labs in Menlo Park is seeking a Forward Deployed Engineer to develop AI-driven simulations for advanced manufacturing. This hands-on role requires strong expertise in numerical simulation and proficiency in Python, as you will engage closely with customer teams onsite.

The position comes with a competitive compensation range of $180,000-$250,000 annually and requires a willingness to travel, particularly to Taiwan. Join us in pushing the boundaries of scientific discovery.

Qualifications

• Strong foundations in numerical simulation of physical systems.
• Hands-on experience building or running simulations.
• Proficiency in Python for scripting.

Responsibilities

• Own the end-to-end simulation workflow with customer teams.
• Build and calibrate physics-based simulations.
• Drive iterative recipe optimization.

Skills

Numerical simulation of physical systems

Python for scripting and automation

Strong communication skills

Comfort working with customer engineering teams

Self-starter orientation

Education

Bachelor's degree in a relevant field

Tools

OpenFOAM

ANSYS Fluent

Star-CCM+

Job description

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

Periodic Labs is deploying AI-driven simulation to solve some of the hardest physical process optimization problems in advanced manufacturing. As a Forward Deployed Engineer focused on physics and simulation, you will be the technical engine behind our most demanding customer engagements — spending significant time on-site, embedding directly with customer teams, and owning the end-to-end simulation workflow that makes our platform work in the real world.

You will work alongside our internal modeling and ML teams to build, calibrate, and iterate on physics-based simulations, translate customer process knowledge into computational models, and drive iterative recipe optimization with direct feedback loops to production. This is a hands-on, high-ownership role at the frontier of AI for physical science.

Willingness to travel to and spend extended time on-site in Taiwan is required.

You Will Thrive in This Role If You Have

• Strong foundations in numerical simulation of physical systems — whether fluid dynamics, heat transfer, structural mechanics, electromagnetics or related domains — gained through graduate research, industry, or both
• Hands-on experience building or running simulations that solve partial differential equations, including comfort with mesh generation, solver tuning, and debugging numerical instabilities
• Proficiency in Python for scripting, automation, and scientific computing (NumPy, SciPy, or equivalent)
• A process engineering or physics mindset: you understand that simulations are tools for answering real process questions, and you care about getting physically meaningful results, not just running jobs
• Strong communication skills and genuine comfort working directly with customer engineering teams — translating between computational models and manufacturing realities
• Willingness to spend extended periods on-site with customers, including in Taiwan
• A self-starter orientation: you can own a technical problem from problem definition through to a deployed result, with limited hand-holding

Especially Strong Candidates May Also Have

• Background in computational fluid dynamics (CFD), including experience with tools such as OpenFOAM, ANSYS Fluent, Star-CCM+, or custom solvers
• Graduate-level research experience building simulation software — from scratch or on top of existing frameworks — in domains such as mechanical or chemical engineering, weather modeling, astrophysics, materials processing, or similar
• Experience in semiconductor or advanced packaging processes (underfill, flip-chip, wafer bonding, or related)
• Familiarity with physics-informed ML, surrogate modeling, or neural operators applied to simulation acceleration
• Experience integrating simulation tools into larger software platforms or automated optimization pipelines
• Proficiency in Mandarin, which would be a meaningful advantage for on-site collaboration in Taiwan
• Some background in a lab or experimental environment, with an appreciation for how simulations relate to physical process data

Mechanics

Minimum education: bachelor’s degree or an equivalent combination of education and training or experience

Location: Our lab is located in Menlo Park and we prefer folks to be located in Menlo Park or San Francisco but can be flexible based on role

Compensation: The annual compensation range for this role - $180,000-$250,000

Visa sponsorship: Yes, we sponsor visas and will do everything we can to assist in this process with our legal support.

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.