WFH.teamOpen app$125k-$250k
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Decision details from the source listing
A master’s degree or PhD is preferred, or substantial professional experience in a relevant engineering discipline.
flexible
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What this posting tells you
Remote contractor role creating engineering tasks and evaluating AI-generated technical work. The listing gives an output-based rate of $60–$120/hour equivalent, paid per accepted task; task availability and completion time may vary, so total earnings are unclear. The role expects 15+ hours per week and a flexible schedule. Country eligibility must be confirmed on the official posting.
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Eligible countries are not stated.
Global
Experienced professional; seniority level not specified · Contractor
- Eligible hiring countries are not stated
Backend hiring on WFH.team
This role's listed pay is near the median among 200 comparable roles shown here. Category counts come from WFH.team's latest published remote job market snapshot.
Explore the remote job marketAI Trainer (Engineering Sciences) at micro1
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 Computational Engineers 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 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 computational engineering 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
Prior paid experience training, evaluating, benchmarking, or improving AI systems on engineering or technical tasks.
Deep expertise in at least one relevant engineering specialization.
Strong programming or scripting ability, with Python strongly preferred.
Hands-on experience using computational methods for engineering analysis, simulation, modeling, optimization, testing, automation, or data processing.
Experience creating or validating technical results with clear and reproducible answers.
Relevant specializations may include mechanical and aerospace engineering, electrical and computer engineering, electronics and embedded systems, chemical and process engineering, civil and structural engineering, manufacturing and industrial engineering, robotics and controls, energy systems, 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
Public engineering code, scripts, models, or simulations
Open-source hardware or engineering-software contributions
Engineering competition results
Reproducible notebooks, benchmarks, 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.
A master’s degree, PhD, or substantial professional experience in a relevant engineering discipline.
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
Submit your application, AI-training experience, 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.
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.