Engineering Simulation & Python Specialist

About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are seeking Computational Engineering Specialists to support a frontier AI initiative focused on developing realistic, terminal-based scientific and technical tasks for training and evaluating AI agents. You will translate authentic engineering workflows into reproducible computational challenges involving simulation, numerical modeling, optimization, data processing, debugging, and technical validation across multiple engineering disciplines.
This role is suited to experienced engineering professionals with strong scientific programming skills and the ability to design technically rigorous tasks, develop reference solutions, and establish objective grading criteria.
Key Responsibilities
Design realistic, multi-step terminal tasks based on engineering and scientific workflows.
Create engineering datasets, simulation inputs, geometry files, sensor data, design constraints, and configuration files.
Develop expert solutions using Python, C/C++, Julia, MATLAB/Octave, Bash, or relevant engineering software.
Build reproducible, containerized environments with appropriate tools and pinned dependencies.
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 that validate engineering correctness, including units, physical constraints, tolerances, convergence, stability, and boundary conditions.
Debug solver, dependency, workflow, precision, and performance issues.
Document assumptions, requirements, expected outputs, edge cases, and technical validation procedures.
Review task solvability, reproducibility, and scientific accuracy.
Incorporate feedback to improve task quality and evaluation reliability.
Requirements
Ph.D., postdoctoral experience, or equivalent advanced technical experience in an engineering discipline, such as mechanical, electrical, chemical, aerospace, civil, materials, biomedical, robotics, or control systems engineering.
Strong scientific programming experience in Python, C/C++, Julia, MATLAB/Octave, Bash, or a comparable language.
Hands-on experience working in Linux or terminal-based environments.
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, boundary conditions, and technical validation.
Ability to build, debug, and validate reproducible computational engineering workflows.

Work arrangement
No