AI Trainer (Engineering Sciences) at Micro1

About the job

Pay: $60–$120/hour equivalent, paid per accepted task
Location: Global, fully remote
Job Type: Contractor
Time Commitment: 15+ hours per week
Schedule: Flexible
micro1 is looking for Engineering professionals with prior professional AI-training or model-evaluation experience to support a project focused on improving advanced AI systems.
You will use your engineering expertise to create challenging technical tasks, evaluate model-generated work, identify failures, and establish objective standards for correct solutions. This role is intended for candidates who have already completed substantive AI-training work.
What You’ll Work On

- Create realistic engineering tasks involving design, analysis, simulation, testing, manufacturing, debugging, or system integration.

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

- Evaluate model-generated calculations, code, simulations, analyses, and technical deliverables.

- Identify invalid assumptions, incorrect results, integration failures, or reproducibility issues.

Required Qualifications

- Prior paid experience training, evaluating, benchmarking, or improving AI systems.

- Strong practical proficiency with Python or comparable engineering scripting.

- Hands-on expertise in at least one relevant hardware or engineering domain.

- Experience using relevant engineering software, command-line tools, scripting interfaces, configuration files, or programmatic APIs.

Relevant domains may include mechanical and aerospace engineering, electrical and computer engineering, electronics, embedded systems, FPGA or ASIC design, civil and structural engineering, chemical and process engineering, manufacturing and industrial engineering, robotics and controls, materials engineering, energy systems, and medical devices and biomedical engineering.
Public Proof of Skill
Strong applicants should provide evidence such as:

- Designs taken into production

- Simulations validated against test data

- Complex engineering failures personally diagnosed

- Patents, publications, or technical reports

- Open-source hardware or engineering-software contributions

- Engineering competition results

- Public schematics, PCB designs, RTL, simulations, test systems, scripts, or technical projects

Confidential employer or customer materials should not be shared.
Preferred Qualifications

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

- Experience reviewing other AI trainers’ technical submissions.

- Experience with verification and validation, testing, failure analysis, or technical quality assurance.

- Experience with long-horizon or agentic AI evaluations.

- Availability to begin immediately.

Application Process

- Submit your application, AI-training experience, engineering specialization, and public technical evidence.

- Complete an AI interview containing technical and integrity checks.

- Complete a hiring-manager review.

- 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.

Originally posted on Himalayas

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