Lead Computational Mechanics Benchmark Designer

Obsidian; Detroit (MI); On-site; USD 55,000 - 96,000; Full time

Job summary

Obsidian is seeking a Computational Structural & Mechanical Engineering Expert to design graduate-level problems using real scientific workflows. You will craft challenges that require simulations, interpretation of results, and strategic experimentation with open-source tools.

You’ll work with state-of-the-art libraries (FEniCSx, OpenFOAM, Cantera, etc.) and write problem setups, oracle functions, and validators in Python, while refining tasks through iterative testing against AI models.

Qualifications

• Graduate-level training in a STEM field (MS/PhD or equivalent)
• Proven proficiency with at least one listed scientific software library
• Strong Python skills for problem setups, oracle functions, and validators
• Ability to work independently and refine problem designs from feedback
• Comfortable with Linux/terminal and remote compute sandboxes
• Available for 15–20 hours per week

Responsibilities

• Design original graduate-level computational problems based on real scientific workflows
• Run simulations using specialized scientific software and interpret results
• Iterate problem difficulty through testing against cutting-edge AI models
• Refine problems and datasets based on feedback to hit target difficulty
• Cover domains like FE, CFD, multiphysics, and thermodynamics

Skills

Python

Graduate-level expertise

Independent work

Problem-design mindset

Education

MS/PhD in STEM

Tools

FEniCSx/DOLFINx

OpenFOAM

deal.II

MFEM

CalculiX

Elmer FEM

Code_Aster

SfePy

Pyomo

Devito

Cantera

CoolProp

FiPy

Job description

Obsidian is seeking a Computational Structural & Mechanical Engineering Expert to design graduate-level problems using real scientific workflows. You will craft challenges that require simulations, interpretation of results, and strategic experimentation with open-source tools.

You’ll work with state-of-the-art libraries (FEniCSx, OpenFOAM, Cantera, etc.) and write problem setups, oracle functions, and validators in Python, while refining tasks through iterative testing against AI models.