Hardware Engineering AI Training Expert

You will create challenging hardware engineering problems based on realistic industry or research scenarios. You will also develop reference solutions and assess whether each problem and solution is technically sound, reproducible, and independently verifiable.

• Create self-contained engineering challenges with realistic product, system, testing, and reliability constraints.
• Solve problems using engineering calculations, simulations, scripts, experimental reasoning, or other suitable methods.
• Use Python, MATLAB, Simulink, SPICE, Julia, C/C++, and test automation platforms when they help validate results.
• Connect first-principles reasoning with practical engineering decisions and measurable results.
• Evaluate technical work for clarity, sound reasoning, reproducibility, and independent verification.

This is a fully remote, part-time contractor role with flexible scheduling, including weekends if desired. The structured experience level is entry level, and the role also requires the technical background and ownership described below.

• Pay: $60 to $120 per hour equivalent, paid per task that meets the project specifications.
• Schedule: Approximately 15 hours per week, with fewer than 20 hours per week required.
• Location: Open to candidates in Algeria, Argentina, Austria, Bahrain, Bangladesh, Belgium, Brazil, Canada, Chile, Colombia, Denmark, Egypt, France, Germany, Ghana, Greece, India, Indonesia, Italy, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Lebanon, Malaysia, Mexico, Morocco, the Netherlands, Nigeria, Oman, Pakistan, Palestinian Territories, Peru, the Philippines, Portugal, Qatar, Saudi Arabia, Singapore, South Africa, Spain, Sri Lanka, Switzerland, Taiwan, Thailand, Tunisia, the United Arab Emirates, the United Kingdom, the United States, Uzbekistan, and Vietnam.
• Language: Fluent English is required.
• Experience: Significant professional or research experience in hardware engineering, product development, systems integration, testing, validation, reliability, or failure analysis.
• Education: A bachelor's, master's, or PhD in electrical engineering, mechanical engineering, mechatronics, aerospace engineering, systems engineering, applied physics, or a related field is preferred.
• Technical ownership: Experience owning substantial technical work, such as a product or subsystem that reached production, a model validated against physical testing, a test system you developed, or a difficult failure you diagnosed.
• Required working style: Experience with coding agents and the ability to produce clear, quantitative, and independently verifiable technical work.
• Helpful tools: Python, MATLAB, Simulink, SPICE, Julia, C/C++, simulation, experimental reasoning, and test automation.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training work uses human-created examples, evaluations, and feedback to improve how artificial intelligence systems perform. People with strong engineering knowledge are paid to create and review difficult technical examples that help models produce more reliable results.