Scientific Computing (Research Engineering Expert)

Crossing Hurdles; United States; Remote; USD 120,000 - 190,000; Full time

Job summary

Crossing Hurdles is seeking a highly qualified engineer to design and develop multi-step, real‑world computational tasks for advanced training and evaluation of AI agents. You will build datasets, inputs, and configurations for complex simulations across multiple engineering domains, using Python, MATLAB/Octave, C/C++, and other tools.

The role emphasizes developing and validating reproducible workflows, automating tests, and creating robust environments with proper dependencies.

Qualifications

• Ph.D. in Engineering or closely related field.
• Expertise across multiple engineering disciplines (e.g., Mechanical, Electrical, Chemical, Aerospace, Civil, Materials, Biomedical, Robotics, Control Systems, Computational Design).
• Strong programming skills in Python, R, Julia, Bash, MATLAB/Octave, C/C++, or equivalent languages.
• Hands-on experience with Linux or terminal-based computational environments.
• Experience with engineering simulation, numerical analysis, optimization, signal processing, control systems, or scientific data analysis.
• Strong understanding of numerical methods, engineering units, physical constraints, boundary conditions, and validation.

Responsibilities

• Design realistic, multi-step scientific and engineering tasks based on real-world computational workflows.
• Develop datasets, simulation inputs, geometry files, sensor data, constraints, and configuration files for engineering problems.
• Build expert solutions using Python, R, Julia, Bash, MATLAB/Octave, C/C++, or relevant engineering tools.
• Develop and validate workflows involving simulation, numerical analysis, optimization, control systems, signal processing, and engineering design.
• Create reproducible computational environments with appropriate tools, dependencies, and configurations.
• Develop automated tests and objective grading criteria to validate engineering correctness, physical constraints, units, tolerances, convergence, and numerical behavior.
• Debug computational, solver, dependency, workflow, and performance issues and document assumptions and edge cases.
• Translate authentic engineering workflows into structured tasks for training and evaluating AI agents.

Education

Ph.D. in Engineering or related field

Tools

Python

R

Julia

Bash

MATLAB/Octave

C/C++

Linux

Job description

Role & Responsibilities:

• Design realistic, multi-step scientific and engineering tasks based on real-world computational workflows.
• Develop datasets, simulation inputs, geometry files, sensor data, constraints, and configuration files for engineering problems.
• Build expert solutions using Python, R, Julia, Bash, MATLAB/Octave, C/C++, or relevant engineering tools.
• Develop and validate workflows involving simulation, numerical analysis, optimization, control systems, signal processing, and engineering design.
• Create reproducible computational environments with appropriate tools, dependencies, and configurations.
• Develop automated tests and objective grading criteria to validate engineering correctness, physical constraints, units, tolerances, convergence, and numerical behavior.
• Debug computational, solver, dependency, workflow, and performance issues and document assumptions and edge cases.
• Translate authentic engineering workflows into structured tasks for training and evaluating AI agents.

Qualifications Required:

• Ph.D. in Engineering or a closely related field.
• Expertise in one or more areas such as Mechanical, Electrical, Chemical, Aerospace, Civil, Materials, Biomedical, Robotics, Control Systems, or Computational Design.
• Strong programming skills in Python, R, Julia, Bash, MATLAB/Octave, C/C++, or equivalent languages.
• Hands-on experience with Linux or terminal-based computational environments.
• Experience with engineering simulation, modeling, numerical analysis, optimization, signal processing, control systems, or scientific data analysis.
• Strong understanding of numerical methods, engineering units, physical constraints, boundary conditions, and technical validation.
• Ability to develop, debug, and validate reproducible computational workflows.

Preferred Candidate Profile:

• Experience with scientific libraries such as NumPy, SciPy, pandas, matplotlib, SymPy, or PyTorch.
• Familiarity with engineering tools such as OpenFOAM, CalculiX, FEniCS, ROS, LTspice, QEMU, or equivalent tools.
• Experience with FEM, CFD, robotics, embedded systems, control systems, or digital twins.
• Familiarity with Docker, Git, CI/CD, automated testing, or HPC environments.
• Experience developing technical benchmarks, simulation-based evaluations, automated graders, or programming tasks.
• Experience evaluating AI coding or terminal-based agents or working in research software engineering.
• Publications, patents, open-source contributions, or industry experience in computational engineering.