🚀 Hiring – AI Trainer (Physical Sciences) | Fully Remote

💼 Job Type :- Full-Time
🌍 Work Mode :- Fully Remote
💰 Compensation :- Up to £64,800 Per Annum

🔬 About the Role

Are you a Computational Physical Scientist with strong expertise in scientific computing, programming and AI model evaluation?

We are looking for highly skilled AI Trainers (Physical Sciences) to contribute to advanced AI development projects. In this role, you will combine your scientific knowledge and programming expertise to design complex scientific challenges, evaluate AI-generated solutions and enhance the scientific reasoning capabilities of next-generation AI systems.

If you have hands-on experience in computational modelling, scientific simulations, numerical analysis or research, this is an exciting opportunity to apply your expertise to cutting-edge AI innovation.

🎯 Key Responsibilities

🧪 Design realistic computational physical-science problems to challenge advanced AI models.

📝 Develop detailed task instructions, reproducible environments, reference solutions and evaluation criteria.

💻 Evaluate AI-generated code, calculations, simulations and scientific analyses.

🔍 Identify numerical errors, incorrect assumptions, methodological flaws and physically impossible results.

📊 Develop benchmarks, grading rubrics and objective technical evaluation standards.

⚙️ Validate computational models and simulations against analytical solutions, experimental data and scientific observations.

✅ Assess the accuracy, reliability and reproducibility of AI-generated scientific outputs.

🎓 Required Qualifications

Prior professional experience in AI training, model evaluation, benchmarking or AI system improvement on scientific or technical tasks.

Strong programming proficiency, particularly in Python.

Deep expertise in at least one relevant physical-science specialization.

Hands-on experience with computational modelling, simulations, numerical analysis or scientific data analysis.

Excellent mathematical, analytical and scientific problem-solving skills.

Experience developing reproducible scientific or research workflows.

🔭 Relevant Specializations

Candidates with expertise in one or more of the following areas are encouraged to apply:

⚛️ Physics & Computational Physics

🌌 Astronomy & Cosmology

🧱 Materials Science

🧬 Chemistry & Computational Chemistry

💻 Scientific Computing & Simulation

📐 Numerical Modelling & Scientific Research

⭐ Preferred Qualifications

Experience creating AI-training tasks, reference solutions, evaluation rubrics, graders or benchmark problems.

Familiarity with scientific computing frameworks and libraries such as NumPy, SciPy, SymPy, Astropy, PyTorch, JAX or equivalent tools.

Experience validating simulations against analytical results, experimental data or scientific observations.

Peer-reviewed publications, preprints or contributions to scientific research.

Contributions to open-source scientific software or computational research projects.

📂 Evidence of Expertise

Candidates are encouraged to share relevant proof of their technical and research expertise, including:

🔗 Google Scholar, ORCID or arXiv profiles.

📚 Peer-reviewed publications or research papers.

💻 GitHub repositories and open-source contributions.

📊 Reproducible notebooks, scientific models, datasets or simulations.

🏆 Public benchmarks, experiments or technical research projects.

🌟 Why Join This Opportunity?

🌍 Work remotely from anywhere.

💡 Contribute to advanced AI development and scientific innovation.

🧠 Apply your research and computational expertise to real-world AI challenges.

🚀 Help improve the scientific reasoning capabilities of next-generation AI systems.

📩 Interested candidates with strong scientific and computational expertise are encouraged to apply!