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Atomic Industries, Inc.

Simulation Engineer

Remote

Location
Remote
Work
Remote
Employment
Not stated
Level
Senior
Function
Engineering
Pay
Not stated
Posted
7 months ago

About the role

About Atomic Industries

Atomic Industries is reinventing how the world makes things. From cars and aerospace systems to medical devices and packaging, most physical goods begin life in a mold or are shaped by a manufacturing tool. Producing these tools has always been slow, manual, and dependent on scarce expertise, taking weeks or months. We’re changing that.

At our Detroit headquarters, we combine the industrial DNA of America’s manufacturing heartland with the speed, intelligence, and precision of Silicon Valley. Our AI-driven platform tackles the hardest problems in geometry, process planning, and fabrication, collapsing production timelines from months to days and soon, minutes. We don’t just build software; we run a fully operational factory where our technology produces production-grade tooling every week, enabling tight feedback loops and rapid iteration.

Backed by top-tier investors, we’re restoring speed, flexibility, and capability to the American industrial base. Our mission is to make manufacturing as agile and scalable as the digital world, and in doing so, rebuild the infrastructure of the physical economy.

About the Role

As a Simulation Engineer at Atomic, you will develop high-fidelity models that capture the physics and constraints of real-world manufacturing processes. From thermomechanical behavior to material flow and force distribution, your work will power the tools that reduce tooling lead times from months to days — and eventually, minutes.

You’ll collaborate with software engineers, generalists, and manufacturing experts to deploy simulation pipelines used every day in production. This role is ideal for someone who blends theoretical rigor with a strong intuition for how things behave in the real world.

What You’ll Do

  • Develop and implement simulations for thermal, structural, and material processes
  • Validate models against physical test data and real production outcomes
  • Work with mesh and CAD data to define simulation-ready geometry representations
  • Integrate solvers and workflows into cloud/on-prem hybrid infrastructure
  • Collaborate with geometry and software teams to inform design and automation logic
  • Optimize simulation runtimes for performance and fidelity

What We’re Looking For

Minimum Qualifications

  • 5+ years of experience with physics-based simulation (FEA, CFD, or related)
  • Deep understanding of mechanical behavior, contact mechanics, heat transfer, or fluid flow
  • Experience with commercial or custom solvers (Ansys, Abaqus, COMSOL, in-house)
  • Proficiency in Python and/or C++
  • Familiarity with geometry formats like B-rep, STL, and volumetric meshes
  • Strong ability to reason from first principles and validate models against the real world

Bonus Points

  • Experience in manufacturing or product design contexts
  • Familiarity with GPU acceleration or distributed compute
  • Background in simulation automation or surrogate modeling
  • Integration of simulation results into design or optimization systems

How We Work

  • Fast iteration: We deploy code daily and validate it in the factory every week
  • Factory-first mindset: Engineers spend time on the shop floor to understand the real-world impact of their work
  • Low ceremony, high ownership: We value well-written design docs, tested code, and real results — not meetings
  • Collaborative culture: Geometry, AI, and robotics teams are tightly integrated and co-develop the product together

Benefits

  • Competitive salary and generous equity package
  • Full medical, dental, and vision coverage for employees and dependents
  • 401(k)
  • PTO with a 15-day minimum
  • Quarterly team travel to Detroit
  • Visa support for TN, E‑3, and O‑1 candidates
  • Hardware stipend and on-site prototype lab access

Source

Posted by Atomic Industries, Inc. on their own hiring page, job-boards.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 11:40 UTC; the original is the reference.

View the original ad ↗

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