We're seeking a Machine Learning Engineer to create structured reasoning traces for AI systems, document decision-making processes, and evaluate AI decision-making workflows. The ideal candidate has a strong background in Machine Learning, Computer Science, or a related field and can articulate complex technical logic with clarity. This is a fully remote, flexible contract role.
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Job Description
Machine Learning Engineer (AI Data Trainer)
About The Role
What if your technical expertise could directly shape how the world's most advanced AI systems learn to reason, plan, and solve real problems? We're looking for Machine Learning Engineers to work alongside leading AI research teams — creating the structured reasoning traces that teach large language models how to think step by step.
This is a fully remote, flexible contract role. If you have a strong background in machine learning or computer science and can articulate complex technical logic with clarity, this is your opportunity to make a lasting impact on the future of AI.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
- Author clear, structured reasoning traces that capture how an AI should plan, decide, and act across complex technical tasks
- Document step-by-step decision-making processes — including tool use, logical branching, and error recovery
- Create high-quality training data that demonstrates effective, reliable problem-solving in real-world scenarios
- Evaluate and improve AI decision-making workflows for accuracy, coherence, and completeness
- Work independently and asynchronously on task-based assignments — fully on your own schedule
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- Strong background in Machine Learning, Computer Science, or a related technical field
- Able to break down complex reasoning into clear, structured, written steps
- Sharp analytical thinker who can evaluate and improve the logic behind AI outputs
- Detail-oriented and consistent — you care about getting the reasoning right
- Comfortable working independently without close supervision
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- Prior experience with data annotation, data labeling, or AI evaluation systems
- Familiarity with LLM prompting, chain-of-thought reasoning, or agent frameworks
- Background in software engineering, applied ML, or AI research
- Experience with tool-augmented or agentic AI workflows
- Work directly with cutting-edge LLMs and the research teams building them
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-impact technical work
- Build rare, hands-on experience in one of the most in-demand areas of AI development
- Potential for ongoing work and contract extension as new projects launch
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