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 Job
We are seeking highly skilled Aerodynamics and Computational Fluid Dynamics (CFD) Specialists with strong programming capabilities to contribute to a specialized AI training project focused on aerodynamic analysis, engineering simulation, and Python-based computational workflows.
This role is particularly suited to engineers who combine a solid understanding of fluid mechanics and applied aerodynamics with practical software development and coding skills. You will create, solve, review, and validate engineering tasks using programmatic, command-line-based workflows.
Typical assignments may involve analyzing airfoils, preparing computational domains and meshes, defining boundary conditions, running CFD simulations, calculating lift and drag, and validating whether resulting flow fields are numerically stable and physically realistic.
Practical coding ability is essential. We are looking for engineers who can actively write Python code, automate engineering workflows, and work with computational tools—not simply candidates who hold relevant academic degrees without the ability to implement technical solutions.
Previous AI experience is not required.
- LOCATION: Remote – US, Canada, Australia, New Zealand, UK, Southeast Asia, and APAC
- WORKLOAD: Approximately 15 hours per week.
- SCHEDULE: Flexible; choose your working days and hours, including weekends.
- COMPENSATION MODEL: Output-based, with payment per task that meets project specifications.
- PROJECT: AI training focused on aerodynamics, CFD, engineering simulation, and Python.
- AI EXPERIENCE: Not required.
Key Responsibilities
- Solve and validate complex aerodynamic and fluid dynamics problems.
- Translate physical engineering requirements into computational models and solver-ready cases.
- Create or modify geometries, computational domains, and meshes.
- Define appropriate initial conditions, boundary conditions, fluid properties, and solver settings.
- Execute CFD and aerodynamic analysis workflows using command-line-accessible tools.
- Write Python code to automate preprocessing, simulation execution, parameter sweeps, postprocessing, and validation.
- Develop scripts and computational workflows for engineering analysis.
- Calculate and interpret aerodynamic quantities, including lift, drag, pressure distributions, and flow characteristics.
- Evaluate mesh quality, numerical convergence, solver stability, and physical validity of simulation results.
- Diagnose non-convergence, unstable solutions, incorrect results, and physically invalid outputs.
- Select and justify modeling assumptions, mesh strategies, boundary conditions, and solver configurations.
- Document technical methodologies, engineering decisions, and simulation results.
Requirements
- Candidates should meet one of the following educational pathways:
Pathway 1: Master's or PhD in Aerospace Engineering, or Mechanical Engineering with a specialization in aerodynamics, fluid dynamics, or thermofluids.
Pathway 2: Bachelor's degree in Aerospace Engineering or Mechanical Engineering, combined with at least 1–2 years of relevant aerodynamics-specific professional or research experience.
- Additional requirements:
Strong understanding of fluid mechanics and applied aerodynamics.
Practical experience formulating and executing CFD or aerodynamic analyses.
Strong practical proficiency in Python, including the ability to write and debug code independently.
Experience using Python for scientific computing, engineering automation, or computational analysis.
Experience with at least one engineering tool or library accessible through a command-line interface, scripting interface, configuration files, or programmatic API.
Ability to select and justify modeling assumptions, boundary conditions, mesh strategies, and solver settings.
Ability to diagnose numerical convergence issues, unstable solutions, and physically invalid results.
Strong quantitative, analytical, and problem-solving skills.
Ability to communicate technical reasoning and engineering trade-offs clearly.
Professional English proficiency at C1 level or higher.
