Principal Mechanical Systems Simulation Engineer

Principal Mechanical Systems Simulation Engineer

Remote / Hybrid · HQ Allentown, PA · Seed Stage

Read the overview of this opportunity to understand what skills, including and relevant soft skills and software package proficiencies, are required.

About 4MP

At 4MP, we are building a new technological foundation for precision manufacturing. Our systems enable CNC machines to self-measure, self-correct, and continuously improve their performance - transforming conventional machine tools into autonomous precision systems.

Backed by a leading institutional investor, and extensively vetted by recognized experts across industry and government laboratories, 4MP is at the beginning of a category-defining journey. We are transitioning from early development into building a visionary company that will redefine how precision manufacturing is done globally.

About the Role

You will join 4MP's cutting-edge simulation team as the Principal Engineer focused on mechanical systems simulation. Mechanical elements deflect, flex, and wear once they are loaded in service, across far more geometry and material combinations than anyone can test one-by-one. You own the physics that predicts that behavior and the code that expresses it, covering the vast space of combinations that can never be tested directly.

This is a software development role, not an FEA analyst role: we are hiring the engineer who writes the solvers, not someone who sets up studies in a commercial package and delivers reports. The domain is solid mechanics and materials characterization, not process mechanics - a component treated as a structure whose response to load varies with size, geometry, material, and operating conditions. At this seed stage you are the technical authority on this physics, you write the code that expresses it, and you work closely with the rest of the engineering team to integrate that work into the platform. You are accountable for whether the predictions hold up against measurement.

What You Will Do

• Model Structural Response Under Load: Treat the component as a structural element - think a loaded shaft - and predict deflection and load-induced positional error as a function of size, geometry, and material properties.
• Characterize Material Behavior: Derive stiffness, damping, and wear/loss characteristics from real test data, and build models that generalize to untested materials and geometries.
• Parameterize and Sweep at Scale: Build the tooling that drives simulations across component size, material, operating speed, and load and engagement conditions. The combinatorics are enormous; the software must cover that space efficiently rather than replicate individual tests.
• Build the Simulation Data Pipeline: Produce and manage large, well-structured simulation datasets - schemas, provenance, reproducibility - and define the sampling strategy that makes the resulting library most useful downstream.
• Validate Against Measurement: Compare predictions to real test and metrology data, and iterate until they are quantitatively reliable - with stated uncertainty, not qualitative agreement.
• Write the Solvers: Derive the governing equations and implement them yourself in production code - discretization, linear algebra, integration, optimization. Commercial packages are references and cross-checks here, not the deliverable.
• Build Production Software: Write real code, not throwaway scripts: modular and tested against analytical and experimental benchmarks, reviewed, packaged, and documented well enough for teammates to use and extend.
• Engineer for Performance: Profile and optimize the hot paths - vectorization, parallelism, compiled extensions, GPU where it pays - so that sweeps of thousands of permutations run in hours, not weeks.
• Work Within a Cutting-Edge Simulation Team: Sit alongside the engineers who own optical sensing and experimental validation, and computational geometry and sensor simulation - you own the mechanical systems simulation domain and the interfaces to theirs, separating structural effects from sensing effects.
• Integrate With the Platform: Work closely with the software, geometry, and sensing engineers so your models plug into the broader codebase and follow shared conventions - not standalone scripts on your own machine.
• Shape the Simulation Roadmap: In coordination with the rest of the team, help decide which components, materials, and conditions to sample, and where to build versus buy.
• Share Depth With the Team: Mentor colleagues on the mechanics and the numerics, review their models, and document your assumptions so others can build on and challenge your work.

What We Require

• 10+ Years of Experience: Deep, hands-on background in structural mechanics, materials characterization, or physics-based simulation of real mechanical systems.
• Principal-Level Ownership: A track record of owning a technical domain end-to-end - scoping ambiguous problems, choosing the approach, and being the person the team relies on for the answer.
• Professional Software Development: Years of writing and shipping production code in a shared codebase - version control, testing, code review, CI, packaging, and debugging software other people depend on. This is a requirement, not a nice-to-have.
• Physics-First Modeling: Demonstrated ability to derive governing mechanics, implement them in code, and validate against measurement - rather than operating a simulation package as a black box.
• Solid Mechanics Depth: Beam and structural deflection theory, elastic-plastic deformation under load, and material constitutive behavior.
• Material Characterization: Experience deriving stiffness, damping, and wear behavior from test data and generalizing it across geometries and operating conditions.
• Numerical Methods in Code: Implementing numerical methods yourself - discretization, linear algebra, time integration, root finding, optimization - with judgment about stability, conditioning, and convergence.
• Collaborative Engineering: Experience working inside a shared team codebase - integrating against interfaces owned by others, following common conventions, and writing code that teammates can pick up and extend.
• Performance Engineering: Profiling and optimizing numerical code - vectorization, memory layout, parallel and multi-core execution, compiled extensions such as C++, Cython, Rust, or Fortran, and GPU or CUDA where warranted.
• Python at Depth: Expert-level Python and the scientific stack - NumPy, SciPy, and the surrounding tooling - not scripting-level familiarity. Comfort orchestrating large parameter sweeps and managing the resulting data.
• Validation Discipline: A track record of closing the loop between simulation and physical measurement, including quantifying model error.
• Educational Foundation: Master's or PhD in Mechanical Engineering, Engineering Mechanics, Physics, Applied Mathematics, or a related field - or a Bachelor's with equivalent depth of hands-on modeling experience.

What Will Set You Apart

• Published or Patented Work: Peer-reviewed publications, patents, or open-source contributions in structural mechanics, materials modeling, or simulation methods.
• Surrogate Modeling: Building fast reduced-order or surrogate models that stand in for expensive simulation inside a production loop.
• Rotordynamics and Vibration: Dynamic response of rotating shafts and components, including damping, modal behavior, and stability.
• Thermal-Structural Coupling: Machine-structure effects such as thermal growth and its interaction with structural deflection.
• Geometry Parameterization: Component-geometry parameterization - size, shape, mass distribution - and its effect on deflection and structural response.
• FEA Fluency as Background: Working knowledge of commercial FEA - enough to use it as an independent cross-check on your own solvers. Valued as background depth, not as the job.
• Open-Source Scientific Software: Contributions to or maintenance of a scientific computing library, solver, or simulation framework used by people outside your own team.
• Compute Infrastructure: Running simulation workloads on clusters or cloud - job orchestration, containerization, and cost-aware scaling.
• Industrial Context: Familiarity with machine tools, industrial equipment, process controls, or precision metrology.
• Startup Experience: Comfort building in an agile, ambiguous environment where the playbook does not exist yet and the first version has to work.
• Technical Influence: Experience being the voice of the physics in the room - with engineering leadership, customers, or national laboratory partners.
• Ownership Drive: You are not looking for a title; you want to own a physics foundation that a new category of manufacturing is built on.

This is a software development role. Applicants whose simulation experience consists of running commercial FEA packages, without a track record of writing and shipping their own code, will not be considered.

Applicants without hands-on experience modeling physical systems and validating those models against measurement will not be considered.

Please do not email resumes or applications directly. xhyhwjd We review candidates exclusively through this job posting.