Use hands-on mechanical engineering technology experience to create realistic AI benchmark tasks, technical datasets, diagnostic pathways, and rigorous evaluation rubrics. This remote contractor role offers output-based work at $30 to $70 per hour.
About OpenTrain
OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. OpenTrain AI is recruiting and contracting for this remote opportunity, helping experienced professionals apply their expertise to projects that shape advanced artificial intelligence systems.
Create a free OpenTrain account to build a professional AI training profile, discover relevant projects, and apply in minutes. Your completed work can help you develop a durable portfolio in a fast-growing technical field.
- Remote contractor opportunity
- Part-time workload of 20 or more hours per week
- English-language work
- Output-based payment for tasks meeting project specifications
About AI Training Work
AI training is the human work behind modern artificial intelligence. Domain experts create examples, review outputs, and develop evaluation systems that help AI models reason more accurately and respond more reliably.
In this role, your mechanical engineering judgment will help turn authentic testing and production scenarios into structured benchmark tasks. The resulting procedures, datasets, solution pathways, and rubrics are designed for use by both AI systems and technical experts.
- Contribute to cutting-edge AI development
- Apply professional expertise to realistic technical scenarios
- Work remotely with flexible, output-focused task assignments
- Help evaluate how advanced AI systems interpret engineering evidence
The Role
As a Mechanical Engineering AI Benchmark Technician, you will create realistic technical tasks and evaluation materials based on laboratory, testing, and production challenges. You will translate professional mechanical engineering technology practice into benchmark workflows covering test setup, instrumentation, data collection, failure diagnosis, data interpretation, and next-step recommendations.
This is a remote contractor role involving output-based task work. Compensation ranges from $30 to $70 per hour, with payment for completed tasks that meet project specifications. Minimum weekly task submission requirements apply, and workload may vary with task complexity and your workflow.
- Subject area: Mechanical Engineering Benchmark Evaluation
- Pay range: $30 to $70 per hour
- Workload: 20 or more hours per week
- Employment type: Contractor and part time
- Experience level listed for the project: Entry level
What You’ll Do
You will design benchmark materials that reflect professional complexity rather than simplified textbook examples. Your work should connect test evidence to technically sound diagnoses, documented procedures, and practical recommendations.
- Design authentic technician workflow tasks based on laboratory, testing, or production challenges.
- Construct technical datasets from test logs, calibration records, sensor outputs, and failure reports.
- Define accurate solution pathways that interpret test data and recommend informed next steps.
- Create evaluation rubrics with at least 35 items covering instrumentation logic, data interpretation, and failure analysis.
- Document technical procedures, observations, diagnostic findings, outcomes, and failure modes precisely.
- Ensure evaluation tasks reflect realistic professional complexity.
- Distinguish likely failure causes from available test evidence.
Requirements
This role requires hands-on mechanical engineering technology experience in laboratory, testing, or production environments. You should be comfortable working with instrumentation and technical records while independently producing clear, rigorous benchmark materials.
- At least four years of hands-on experience in mechanical engineering technology environments.
- Extensive experience with instrumentation, sensors, data acquisition systems, and prototype testing workflows.
- Strong analytical ability to interpret complex datasets and diagnose equipment or process failures.
- Skill in documenting test procedures, observations, outcomes, diagnostic findings, and failure modes.
- Ability to design realistic benchmark tasks and rigorous evaluation rubrics with 35 or more items.
- Familiarity with CSV files, spreadsheets, PDFs, and related technical documentation formats.
- Ability to work independently while meeting demanding technical standards.
- An associate degree or recognized trade credential in mechanical engineering technology or a related discipline is preferred.
Who Should Apply
This opportunity is suited to mechanical engineering technicians and related professionals who understand how real testing workflows operate and can explain technical reasoning clearly. Experience developing technical exercises, interpreting calibration or sensor records, and diagnosing failures from test evidence can help you produce stronger benchmark tasks.
The project is listed as entry level, but the role description requires substantial hands-on experience and specialized instrumentation knowledge. Clear technical communication is essential because your procedures, solution pathways, and rubrics must be usable by both domain experts and AI systems.
- Mechanical engineering technology professionals
- Laboratory, testing, production, or prototype-testing practitioners
- Technicians experienced with sensors and data acquisition systems
- Professionals who can convert technical evidence into structured evaluation criteria
- Independent contractors comfortable with output-based project work
How the Work Fits Your Schedule
The role is remote and part time, with a minimum weekly task submission requirement. You will complete output-based assignments, and the amount of work may vary according to the complexity of each task and your workflow.
OpenTrain supports flexible participation in AI training work, allowing contributors to apply specialized expertise from wherever they are eligible to work with a computer and internet connection.
- Minimum commitment: 20 or more hours per week
- Remote work format
- Variable workload based on task complexity
- Payment tied to tasks that meet project specifications
