Scientific Computing / Research Engineering Expert – Engineering | Remote

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Scientific Computing / Research Engineering Expert – Engineering | Remote A frontier AI initiative is looking for experienced Engineering and Scientific Computing professionals to develop realistic, terminal-based technical and scientific tasks used to train and evaluate AI agents. This is a 5-week remote contractor opportunity for professionals with strong engineering, programming, simulation, modeling, and technical validation experience. 💼 Job Details Position: Scientific Computing / Research Engineering Expert – Engineering Work Type: Remote Employment Type: Contractor Assignment Contract Duration: 5 weeks Expected Start: Next week Commitment: At least 6 hours per day / 40+ hours per week PST Overlap: 4 hours Payment: $300 per approved task Paid Leave/Medical Benefits: Not included 🔬 About the Role The role focuses on converting real-world engineering workflows into reproducible computational tasks that test AI agents on modeling, simulation, optimization, debugging, data processing, and technical validation. The work can cover multiple engineering disciplines, including: Electrical Engineering Mechanical Engineering Chemical Engineering Aerospace Engineering Civil Engineering Materials Engineering Biomedical Engineering Robotics Control Systems 🛠️ Responsibilities Selected experts will: Design realistic, multi-step engineering tasks based on real-world workflows. Create engineering datasets, simulation inputs, geometry files, sensor data, and configuration files. Develop expert solutions using Python, C/C++, Julia, MATLAB/Octave, Bash, or relevant engineering software. Build reproducible and containerized computational environments. Develop tasks involving simulation, numerical analysis, optimization, control systems, signal processing, FEM concepts, CAD-related data, and engineering design. Create automated tests and objective grading criteria. Validate engineering units, physical constraints, tolerances, convergence, stability, and numerical behavior. Debug solver, dependency, workflow, precision, and performance issues. Document assumptions, requirements, expected outputs, and edge cases. 🎓 Requirements Candidates should have: Ph.D., postdoctoral experience, or equivalent advanced technical experience in an engineering discipline. Strong programming skills in Python, C/C++, Julia, MATLAB/Octave, Bash, or another relevant language. Experience working in Linux or terminal-based environments. Hands-on experience with engineering simulation, modeling, numerical analysis, optimization, signal processing, control systems, or technical data analysis. Strong understanding of numerical methods, engineering units, physical constraints, and technical validation. Ability to build, debug, and validate reproducible computational workflows. ⭐ Nice to Have Experience with: NumPy, SciPy, pandas, matplotlib, SymPy, PyTorch OpenFOAM, CalculiX, FEniCS, ROS, LTspice-compatible workflows Finite-element methods (FEM) Computational fluid dynamics (CFD) Robotics and embedded systems Control systems and digital twins Docker, Git, CI/CD, automated testing, or HPC Technical benchmarks and automated graders AI coding or terminal-agent evaluation Research software engineering Computational engineering publications, patents, open-source projects, or industry experience 💰 Compensation $300 per approved task This opportunity is suitable for experienced engineering professionals who want to contribute their technical expertise to AI training and evaluation. Apply Now