AI Trainer (Engineering Sciences)

1. Create realistic computational engineering tasks that challenge advanced AI models.
2. Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
3. Evaluate model-generated code, calculations, simulations, designs, analyses, and technical deliverables.

1. Prior paid experience training, evaluating, benchmarking, or improving AI systems on engineering or technical tasks.
2. Deep expertise in at least one relevant engineering specialization.
3. Strong programming or scripting ability, with Python strongly preferred.
4. Hands-on experience using computational methods for engineering analysis, simulation, modeling, optimization, testing, automation, or data processing.
5. Experience creating or validating technical results with clear and reproducible answers.

Relevant specializations may include mechanical and aerospace engineering, electrical and computer engineering, electronics and embedded systems, chemical and process engineering, civil and structural engineering, manufacturing and industrial engineering, robotics and controls, energy systems, and biomedical engineering.

Strong applicants should provide evidence such as:

1. Designs taken into production
2. Simulations validated against test data
3. Complex engineering failures personally diagnosed
4. Patents, publications, or technical reports
5. Public engineering code, scripts, models, or simulations
6. Open-source hardware or engineering-software contributions
7. Engineering competition results
8. Reproducible notebooks, benchmarks, or technical projects

Confidential employer or customer materials should not be shared.

1. Experience creating AI-training tasks, reference solutions, rubrics, graders, or benchmark problems.
2. Experience reviewing other AI trainers’ technical submissions.
3. A master’s degree, PhD, or substantial professional experience in a relevant engineering discipline.
4. Experience with command-line tools, scripting interfaces, configuration files, solver APIs, or programmatic engineering software.
5. Experience validating computational results against calculations, simulations, measurements, or physical tests.
6. Prior experience with long-horizon or agentic AI evaluations.
7. Availability to begin immediately.

1. Submit your application, AI-training experience, specialization, and public technical evidence.
2. Complete an AI interview containing technical and integrity checks.
3. Complete a hiring-manager review.
4. If selected, complete project onboarding and begin your first assigned task.

1. Compensation is output-based. Experts are paid for tasks that meet project specifications and quality requirements. Task availability and completion time may vary.