Forward Deployed Engineer, Physics & Simulation

Reposted 18 Days Ago
Be an Early Applicant
Menlo Park, CA, USA
In-Office
180K-250K Annually
Mid level
Artificial Intelligence • Hardware • Information Technology • Robotics
From bits to atoms.
The Role
As a Forward Deployed Engineer, you will manage customer simulation workflows, implement physics-based simulations, collaborate with engineering teams, and integrate findings into real-world applications while traveling to customer locations.
Summary Generated by Built In
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

We’re using AI-driven simulation to solve hard physical process optimization problems in advanced manufacturing. As a forward deployed engineer focused on physics and simulation, you will be the technical backbone of our most demanding customer engagements – spending significant time on-site, embedding directly with customer teams, and owning simulation workflows end-to-end.

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

This role requires travel to and extended time on-site in Taiwan.

What You’ll Do
  • Own the simulation workflow end-to-end for customer engagements, from model setup and calibration through optimization and results interpretation

  • Run, debug and modify physics-based simulations of complex physical processes in diverse domains, such as microfluidics, charge transport and structural deformation

  • Work on-site with customer engineering teams on-site to understand process constraints, interpret simulation results into real process improvements

  • Write tools, skills and agents to reliably drive end-to-end LLM-based simulation workflows, including experimental validation, parameter fitting and recipe optimization

  • Build and extend simulation tooling in Python – job submission, parameter sweeps, output parsing, integration

  • Feed domain insights back to the research and product teams, shaping the next version our platform

You Will Thrive in This Role If You Have
  • A strong foundation in numerical simulation of continuum systems – fluid dynamics, heat transfer, structural mechanics, electromagnetics, or similar – gained through graduate research, industry, or both

  • Hands-on experience solving partial differential equations numerically, including mesh generation, solver tuning, and debugging numerical instabilities

  • Solid Python skills for scripting and scientific computing (NumPy, SciPy, or similar)

  • A process engineer’s instinct: you treat simulations as tools for answering real process questions, not just jobs to run

  • Strong communication skills and genuine comfort working directly with customer engineers

  • Willingness to spend extended periods on-site in Taiwan

  • A self-starter mindset: you can take a technical problem from definition to deployed result without much hand-holding

Especially Strong Candidates May Also Have
  • CFD background, including tools like OpenFOAM, ANSYS Fluent, Star-CCM+, or custom solvers

  • Grad-level research experience building simulation software in domains like mechanical or chemical engineering, weather modeling, astrophysics, or materials processing

  • Familiar with semiconductor manufacturing processes

  • 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

  • Mandarin proficiency for on-site collaboration in Taiwan

  • Lab or experimental background, with an appreciation for how simulation connects to physical data

Mechanics

Minimum education: Bachelor’s degree or similar experience

Location: Menlo Park, CA (Soon: San Francisco, too) + frequent travel to Taiwan

Compensation: $200,000-$275,000 + equity

Visa sponsorship: Yes, we sponsor visas.

Skills Required

  • Strong foundations in numerical simulation of physical systems
  • Hands-on experience building or running simulations for partial differential equations
  • Proficiency in Python for scripting and scientific computing
  • Comfortable working with customer engineering teams
  • Willingness to spend extended time on-site with customers
  • Bachelor's degree or equivalent experience
Am I A Good Fit?
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The Company
32 Employees
Year Founded: 2025

What We Do

We're building AI scientists and the autonomous laboratories for them to operate.

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