Scientific Computing AI Task Designer

The work

OpenTrain is hiring a Scientific Computing and Engineering AI Task Designer to turn real engineering workflows into reproducible terminal-based tasks. These tasks will train and evaluate AI agents across modeling, simulation, optimization, data processing, debugging, and technical validation.

You will work across areas such as mechanical, electrical, chemical, aerospace, civil, materials, biomedical, robotics, and control systems engineering. Your work should reflect realistic technical problems and produce clear, testable results.

• Design multi-step terminal tasks based on real scientific and engineering workflows.
• Create datasets, simulation inputs, geometry files, sensor data, design constraints, and configuration files.
• Develop expert solutions with Python, C or C++, Julia, MATLAB or Octave, Bash, and relevant engineering software.
• Build containerized environments with suitable tools and pinned dependencies.
• Write automated tests and objective grading criteria for units, physical constraints, tolerances, convergence, stability, boundary conditions, and numerical behavior.
• Debug solver, dependency, workflow, precision, and performance problems.
• Document assumptions, expected outputs, edge cases, and technical validation steps.

What it pays and takes

This is a remote contractor assignment lasting approximately five weeks. The work requires advanced technical judgment, strong scientific programming, and hands-on experience working in Linux or terminal environments.

• Pay: $300 per approved task.
• Schedule: At least 40 hours per week, with four hours of overlap with Pacific Time.
• Work arrangement: Remote and open worldwide.
• Language: English.
• Experience: A Ph.D., postdoctoral experience, or equivalent advanced technical experience in an engineering discipline.
• Required skills: Scientific programming, Linux or terminal work, numerical methods, engineering units, physical constraints, boundary conditions, and reproducible technical validation.
• Useful tools and background: NumPy, SciPy, pandas, matplotlib, SymPy, PyTorch, OpenFOAM, CalculiX, FEniCS, ROS, LTspice-compatible workflows, QEMU, Docker, Git, CI/CD, automated testing, or HPC environments.
• Relevant experience may include finite-element methods, computational fluid dynamics, robotics, embedded systems, control systems, digital twins, technical benchmarks, simulation-based evaluation, automated graders, or AI coding agent evaluation.
• Publications, patents, open-source contributions, or computational engineering industry experience are welcome.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training work is the human side of building artificial intelligence. People create examples, review model behavior, and test whether AI systems can solve real problems, so advanced technical experience is valuable when tasks require accurate code, simulations, and engineering judgment.