STEM Computational Problem Creation Expert

hackajob; Remote; GBP 60,000 - 80,000; Part time

Job summary

A leading AI platform is seeking a STEM Computational Problem Creation Expert to design deterministic, computationally intensive STEM problems for AI training and evaluation. Ideal candidates will have a strong Python background and an MSc or PhD in a relevant field. Responsibilities include creating original problems, validating solutions, and ensuring numerical accuracy. This remote, independent contract offers flexibility and requires at least 5 years of problem-solving experience.

Qualifications

• 5+ years of computational or numerical problem-solving experience.
• Experience validating numerical or algorithmic results.

Responsibilities

• Design and verify original computational STEM problems.
• Create deterministic computational problems that require Python.
• Implement and validate Python reference solutions.
• Document inputs, methods, constraints, and expected outputs.
• Verify numerical and algorithmic correctness.

Skills

Python

Numerical methods

Simulations

Optimization

Education

MSc or PhD in Physics

MSc or PhD in Applied Mathematics

MSc or PhD in Engineering

MSc or PhD in Scientific Computing

Tools

NumPy

SciPy

Pandas

Job description

STEM Computational Problem Creation Expert (Remote, Contract)

Independant contract | Flexible | Remote

hackajob is partnering with a leading AI platform to support the development of advanced AI evaluation and training datasets.

We’re onboarding senior STEM experts to design fully deterministic, computationally intensive STEM problems used to train and evaluate next-generation AI systems.

What You’ll Do

You’ll design and verify original computational STEM problems that simulate real scientific and engineering workflows.

Your responsibilities include:

• Creating deterministic computational problems that require Python to solve
• Ensuring each problem has one correct, reproducible output
• Implementing and validating Python reference solutions
• Clearly documenting:
• Inputs
• Methods
• Constraints
• Expected outputs
• Verifying numerical and algorithmic correctness

This role is ideal for professionals who enjoy numerical methods, simulations, optimization, and exact problem-solving.

Example Problem Types

• Numerical integration with fixed boundary conditions
• Deterministic Monte Carlo simulations (fixed seeds)
• Combinatorial or graph enumeration
• Optimization problems with a unique global optimum
• Physics or engineering simulations with fully specified parameters

This role is about precision, determinism, and verification.

Ideal Background

• MSc or PhD in:
• Physics
• Applied Mathematics
• Engineering
• Scientific Computing

5+ years of computational or numerical problem-solving experience

Strong Python skills (NumPy, SciPy, Pandas; sklearn where relevant)

Experience validating numerical or algorithmic results

Strong bonus if you have:

• Research or post-doctoral experience
• HPC or simulation-heavy work**Utility functions** We are given two anyone?…????..???.. We need..??……… This…..? ...….. ...??? ?????…..?……?…..… Scrolling? Wait. The prompt incomplete? maybe incorrectly parsed. Let's open alc court? : The problem statement maybe from another source. Let's guess: