What if your expertise in computational fluid dynamics could teach AI to reason about aerodynamics, boundary conditions, and flow physics - without you ever having to write a single line of machine-learning code?
We're looking for CFD engineers and aerodynamicists to design small, well-defined engineering challenges that train and evaluate AI models on real fluid-dynamics reasoning. Each task you create has three parts: a clear problem statement, a deterministic checker that scores the model's answer, and a trusted reference solution that proves the task is solvable. Think of it as writing bite-sized CFD exam problems - grounded in physics, unambiguous, and automatically gradable.
No reinforcement-learning or AI research background is required. What matters is your hands-on simulation experience and your ability to translate domain knowledge into precise, solvable tasks.
Organization : Alignerr
Type : Hourly Contract
Location : Remote
Commitment : 10-40 hours/week
What You'll Do
Design compact, self-contained CFD and aerodynamics tasks that test an AI model's engineering reasoning
Write clear, unambiguous problem statements covering topics such as boundary-condition selection, mesh quality assessment, flow-regime identification, and simulation setup
Develop deterministic scoring checkers that can automatically evaluate a model's final answer
Provide verified reference solutions that confirm each task is solvable and correctly scored
Review and iterate on tasks to ensure physical accuracy, clarity, and appropriate difficulty
Draw on your experience with OpenFOAM to ground tasks in real-world practice
Work independently and asynchronously - fully on your own schedule
Who You Are
Hands-on experience with OpenFOAM
Solid foundation in fluid mechanics, aerodynamics, and heat transfer fundamentals
Comfortable with mesh generation, turbulence modeling, boundary-condition specification, and post-processing
Able to formulate engineering problems that are precise, self-contained, and objectively verifiable
Strong written communication skills in English - you can explain complex physics clearly and concisely
Background in Aerospace Engineering, Mechanical Engineering, Strömungsmechanik, or a closely related discipline (BSc or higher preferred)
Self-motivated and reliable when working independently without supervision
Nice to Have
Experience across multiple CFD solvers or multiphysics platforms (e.g., ANSYS Fluent, STAR-CCM+, SU2)
Familiarity with scripting or automation (Python, Bash, MATLAB) for setting up or post-processing simulations
Exposure to design optimization, flow-control strategies, or adjoint methods
Graduate-level coursework or research in aerodynamics, propulsion, or computational methods
Previous experience writing technical assessments, exam problems, or engineering challenges
Interest in how large language models reason about STEM problems
Why Join Us
Apply your CFD expertise to cutting-edge AI research alongside leading labs - from a completely new angle
Fully remote and flexible - work when and where it suits you
Freelance autonomy with the structure of meaningful, task-based work
No need to retrain as a data scientist - your engineering judgment is exactly what's needed
Contribute directly to teaching AI models real-world physical reasoning
Potential for ongoing work and contract extension as new projects launch
CFD Engineer - AI Task Designer
About the Role
What if your expertise in computational fluid dynamics could teach AI to reason about aerodynamics, boundary conditions, and flow physics - without you ever having to write a single line of machine-learning code?
We're looking for CFD engineers and aerodynamicists to design small, well-defined engineering challenges that train and evaluate AI models on real fluid-dynamics reasoning. Each task you create has three parts: a clear problem statement, a deterministic checker that scores the model's answer, and a trusted reference solution that proves the task is solvable. Think of it as writing bite-sized CFD exam problems - grounded in physics, unambiguous, and automatically gradable.
No reinforcement-learning or AI research background is required. What matters is your hands-on simulation experience and your ability to translate domain knowledge into precise, solvable tasks.
Organization : Alignerr
Type : Hourly Contract
Location : Remote
Commitment : 10-40 hours/week
What You'll Do
Design compact, self-contained CFD and aerodynamics tasks that test an AI model's engineering reasoning
Write clear, unambiguous problem statements covering topics such as boundary-condition selection, mesh quality assessment, flow-regime identification, and simulation setup
Develop deterministic scoring checkers that can automatically evaluate a model's final answer
Provide verified reference solutions that confirm each task is solvable and correctly scored
Review and iterate on tasks to ensure physical accuracy, clarity, and appropriate difficulty
Draw on your experience with OpenFOAM to ground tasks in real-world practice
Work independently and asynchronously - fully on your own schedule
Who You Are
Hands-on experience with OpenFOAM
Solid foundation in fluid mechanics, aerodynamics, and heat transfer fundamentals
Comfortable with mesh generation, turbulence modeling, boundary-condition specification, and post-processing
Able to formulate engineering problems that are precise, self-contained, and objectively verifiable
Strong written communication skills in English - you can explain complex physics clearly and concisely
Background in Aerospace Engineering, Mechanical Engineering, Strömungsmechanik, or a closely related discipline (BSc or higher preferred)
Self-motivated and reliable when working independently without supervision
Nice to Have
Experience across multiple CFD solvers or multiphysics platforms (e.g., ANSYS Fluent, STAR-CCM+, SU2)
Familiarity with scripting or automation (Python, Bash, MATLAB) for setting up or post-processing simulations
Exposure to design optimization, flow-control strategies, or adjoint methods
Graduate-level coursework or research in aerodynamics, propulsion, or computational methods
Previous experience writing technical assessments, exam problems, or engineering challenges
Interest in how large language models reason about STEM problems
Why Join Us
Apply your CFD expertise to cutting-edge AI research alongside leading labs - from a completely new angle
Fully remote and flexible - work when and where it suits you
Freelance autonomy with the structure of meaningful, task-based work
No need to retrain as a data scientist - your engineering judgment is exactly what's needed
Contribute directly to teaching AI models real-world physical reasoning
Potential for ongoing work and contract extension as new projects launch
What You'll Do
Organization : Alignerr
Type : Hourly Contract
Location : Remote
Commitment : 10-40 hours/week
Design compact, self-contained CFD and aerodynamics tasks that test an AI model's engineering reasoning
Write clear, unambiguous problem statements covering topics such as boundary-condition selection, mesh quality assessment, flow-regime identification, and simulation setup
