We are looking for Domain experts (Engineering/ Mathematics & Statistics/ Physical Sciences/ Software Engineering/ Earth & Environmental Sciences) with prior professional AI-training or model-evaluation experience to support a project focused on improving advanced AI systems.

You will use your domain expertise and programming skills to create challenging technical tasks, evaluate model-generated code and analyses, identify failures, and establish objective standards for correct solutions. This role is intended for candidates who have completed substantive AI-training work involving engineering or other technical content.

What You’ll Work On

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

Required Qualifications
- Masters/ PhD degree in your domain (Engineering/ Mathematics & Statistics/ Physical Sciences/ Software Engineering/ Earth & Environmental Sciences).
- Prior paid experience training, evaluating, benchmarking, or improving AI systems on technical tasks.




- Experience creating or validating technical results with explicit and reproducible answers.

Preferred Qualifications
- Experience creating AI-training tasks, reference solutions, rubrics, graders, or benchmark problems.
- Experience reviewing other AI trainers’ technical submissions.
- Experience with command-line tools, scripting interfaces, configuration files, solver APIs, or programmatic engineering software.
- Experience validating computational results against calculations, simulations, measurements, or physical tests.
- Prior experience with long-horizon or agentic AI evaluations.
- Availability to begin immediately.

Application Process
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.

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

📌 AI Trainer (India)
🏢 NetSysCon Consulting
📍 India