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Data Science micro1

AI Trainer (ML Engineering)

micro1 • Remote

Education

Not stated

Type

Hourly

Pay

$60-120/hr

Your rate depends on your experience and the task.

Actively hiring

100 openings

Checked

Only apply if this role fits your skills and interests.

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About this role

From the micro1 listing

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 Machine Learning Engineers with prior professional AI-training or model-evaluation experience to support a project focused on improving advanced AI systems. You will use your machine learning 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 machine learning engineering tasks that challenge advanced AI models.
  • Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
  • Evaluate model-generated code, experiments, analyses, and technical deliverables.
  • Identify issues involving data leakage, incorrect validation, unstable training, performance, or reproducibility.

Required Qualifications

  • Prior paid experience training, evaluating, benchmarking, or improving AI systems.
  • Strong practical proficiency with Python.
  • Hands-on experience using PyTorch, JAX, TensorFlow, scikit-learn, XGBoost, LightGBM, or comparable ML tools.

Public Proof of Skill

Strong applicants should provide evidence such as:

  • GitHub repositories or public model implementations
  • Kaggle, DrivenData, AIcrowd, or similar competition results
  • Hugging Face models or datasets
  • Research publications or technical reports
  • Open-source ML contributions
  • Public benchmarks, experiments, or technical projects

Preferred Qualifications

  • Experience creating AI-training tasks, reference answers, rubrics, graders, or benchmark problems.
  • Experience reviewing other AI trainers’ technical submissions.
  • Kaggle Expert, Master, or Grandmaster status, or strong results in another technical competition.
  • Publications or open-source contributions in machine learning.
  • Prior experience with long-horizon or agentic AI evaluations.
  • Availability to begin immediately.

Application Process

  • Submit your application, AI-training experience, 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.

Requirements

  • ML Engineering
  • AI training
  • Programming Skills

How long hiring takes

On the platforms we refer people to, half of hires came within about 25 days of applying. Time from applying to hire:

Under 2 weeks
~30%
2 weeks to 6 weeks
~40%
6 weeks to 3 months
~15%
Over 3 months
~15%

AI Trainer interview prep

Questions AI Trainer interviewers often ask. They aren't taken from this listing.

How do you evaluate whether a model's response to a prompt satisfies the instruction, versus just sounding plausible?

I go back to the instruction line by line and check each requirement against the response individually, rather than reading the response holistically and asking if it feels right. A confident, well-written response can still quietly skip a constraint the prompt asked for.

What's your process for writing a rating rubric that two different reviewers would apply the same way?

I define each rating level with a concrete example rather than an abstract description, since two reviewers can read the same adjective differently but usually agree on whether a response matches a given example. I test the rubric on a handful of edge cases with another reviewer before rolling it out.

How do you decide when a prompt itself is ambiguous versus when the model's response is simply wrong?

I ask whether a reasonable person could interpret the prompt more than one way and still be following the instruction correctly. If the response fails under every reasonable reading, it's a model error; if it only fails under one specific reading, the prompt needs to be flagged as ambiguous instead.

How do you document the reasoning behind a rating so someone reviewing your work later understands the decision?

I write a short note pointing to the specific part of the response that drove the rating, so a reviewer can see what I was reacting to. A rating with no reasoning attached is hard to audit and even harder to disagree with productively.

See all 10 AI Trainer interview questions →

Why this role

This AI Trainer (ML Engineering) role pays $60-120/hr for Data Science work, without finding or billing your own clients.

Skills and categories

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Common questions

What does the micro1 application process look like?

You start with a video interview with Zara, micro1's AI interviewer. Treat it like a video call: good light, clear sound and spoken answers to technical questions. A person reviews the recording, and some roles add a short skills test.

Can I apply to micro1 from outside the US or UK?

Yes. micro1 accepts applicants from most countries. Most roles need strong written and spoken English.

What does task-based AI training work look like?

Short, hands-on tasks such as recording videos, sorting images, rating AI answers or checking data. Most take 5 to 60 minutes each.

Can I choose my own hours?

Usually, yes. You log in when you want, pick up a task, finish it and submit it, with no meetings. Other people work from the same pool of tasks, so some days there may be no work until more is added.

What does Data Science work look like for an AI Trainer (ML Engineering)?

You check AI answers to Data Science questions, correct their errors and write expert reasoning. As an AI Trainer (ML Engineering), you're hired for that judgment, so hands-on Data Science experience matters.

What specific skills does this listing call for?

ML Engineering, AI training, and Programming Skills are named directly in the listing. If you don't have hands-on experience with these, expect the screening to test for them.

What does the 'openings' count on this listing mean?

It's how many people micro1 still wants to hire for this role: 100 when we last checked. A high number means more places to fill. The screening stays the same.

How much does this specific role pay?

This listing is posted at $60-120/hr, an hourly rate. Where you land in the range depends on your background and the assessment. Pay can change after we check the listing, so confirm the rate on the platform's application page.

What happens when I click Apply on this listing?

Apply opens micro1's site, where you create an account and follow its sign-up steps.