WFH.teamOpen app$62k-$146k
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Decision details from the source listing
4+ years stated
Associate degree or recognized trade credential in mechanical engineering technology or a related discipline (preferred)
flexible
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What this posting tells you
Remote, output-based contractor role creating realistic mechanical engineering technician tasks, datasets, solution pathways, and grading rubrics for an AI benchmarking project. The listing prefers at least 4 years of hands-on lab, test, or production experience and an associate degree or related trade credential. Compensation is per accepted task, with no pay amount stated; a minimum number of weekly submissions and a rapid start after onboarding are expected.
Customer success, Data, Design and creative, Finance and investments, Operations, Product, QA and testing
Eligible countries are not stated.
Timezone overlap is not stated.
Mid-level · Contractor
- Eligible hiring countries are not stated
- Required timezone overlap is not stated
Customer success hiring on WFH.team
This role's listed pay is below the median among 162 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.
Explore the remote job marketMechanical Engineering Technician at micro1
Role Title: Mechanical Engineering Technician
Role Type: Contractor
Location: Remote
micro1 is engaging Mechanical Engineering Technicians to contribute to a customer's project involving the development of advanced AI benchmarks. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.
Scope of Work
Design and author authentic technician workflow tasks that reflect real-world challenges, including test setup, instrumentation, data collection, and failure diagnosis.
Source, synthesize, and construct technical datasets (such as test logs, calibration records, sensor outputs, and failure reports) derived from actual lab or production scenarios.
Define accurate solution pathways, including the interpretation of test data and informed next-step recommendations.
Develop rigorous, 35+ item grading rubrics to evaluate technical skills in instrumentation logic, data interpretation, and failure analysis, usable by AI and domain experts alike.
Document detailed technical procedures, observations, and diagnostic findings with high precision and clarity.
Ensure all evaluation tasks meet the complexity and realism standards representative of professional practice, surpassing simplified textbook examples.
Preferred qualifications
Minimum 4 years of hands-on experience in lab, test, or production environments within mechanical engineering technology.
Associate degree or recognized trade credential in mechanical engineering technology or related discipline.
Extensive experience with instrumentation, sensors, data acquisition systems, and prototype testing workflows.
Demonstrated ability to perform in-depth technical documentation of test procedures, outcomes, and failure modes.
Strong analytical skills for interpreting complex datasets and diagnosing equipment or process failures.
Familiarity with technical documentation formats, such as CSVs, spreadsheets, PDFs, and other relevant files.
Comfort working independently, contributing to remote projects, and aligning deliverables with high technical standards.
Compensation Structure
Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.
Start Timeline & Availability
We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.
Working remotely at micro1
micro1 builds human-expertise data and evaluation infrastructure for AI models and agents. It recruits core-team employees and domain experts for AI training projects.
- Headquarters
- San Francisco Bay Area, California, United States
- Founded
- 2022
Expert opportunities are remote and can be flexible. International applicants are considered, subject to country exclusions and each project's requirements. Core-team work arrangements vary by opening; check the individual posting.
Apply through the official posting. Expert applicants complete an AI interview and skills certification, followed by project selection and onboarding. Certification does not guarantee a project or immediate work.