Machine Learning Engineer

Job summary

Create structured reasoning traces that demonstrate planning, tool use, problem decomposition, and decision-making for complex technical tasks. Produce and evaluate training data and AI workflows to improve the accuracy and reliability of large language model outputs.

Job details

Machine Learning Engineer (AI Data Trainer) About The Role What if your technical expertise could directly shape how the next generation of AI systems reason, plan, and solve real-world problems? We're looking for Machine Learning Engineers to help train cutting-edge large language models — not by writing model code, but by doing something arguably more impactful: showing AI how to think. This is a fully remote, flexible contract role. You'll work with one of the leading AI research organizations to create structured reasoning traces that teach LLMs to plan, use tools, and make decisions the way a skilled engineer would. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Author clear, structured reasoning traces that document step-by-step planning and decision-making for complex technical tasks Demonstrate effective tool use, problem decomposition, and logical reasoning in written form Create high-quality training data that helps LLMs reason more reliably in real-world scenarios Evaluate and improve AI decision-making workflows to ensure outputs are accurate and well-reasoned Work independently and asynchronously — fully on your own schedule Who You Are Background in Machine Learning, Computer Science, or a related technical field Able to articulate complex logical steps and technical reasoning clearly in writing Strong analytical thinker who naturally breaks problems down into structured, traceable steps Detail-oriented and consistent — you care about quality and precision Comfortable working independently without close supervision Nice to Have Prior experience with data annotation, data labeling, or AI evaluation systems Familiarity with LLMs, prompt engineering, or AI training workflows Background in software engineering, research, or applied ML Experience documenting technical processes or writing technical specifications Why Join Us Work on genuinely cutting-edge AI projects alongside world-leading research labs Fully remote and flexible — work when and where it suits you Freelance autonomy with the structure of meaningful, task-based work Make a direct, tangible impact on how advanced AI systems reason and behave Potential for ongoing work and contract extension as new projects launch Gain rare, hands-on exposure to how frontier LLMs are built and trained

What you’ll do

Create structured reasoning traces that demonstrate planning, tool use, problem decomposition, and decision-making for complex technical tasks. Produce and evaluate training data and AI workflows to improve the accuracy and reliability of large language model outputs.

Requirements

Applicants should have a background in machine learning, computer science, or a related technical field and be able to clearly document complex technical reasoning. Strong analytical skills, attention to detail, and the ability to work independently are required; experience with data annotation, LLMs, or AI evaluation is an advantage.

Benefits

• Fully Remote And Flexible Work
• Freelance Autonomy
• Potential For Ongoing Work And Contract Extension
• Hands-On Exposure To Frontier LLMs

Listed skills

• Decision Making · Preferred
• Machine learning · Preferred
• prompt engineering · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Computer Science
• Structured Reasoning
• Logical Reasoning
• Problem Decomposition
• Tool Use
• Data Annotation
• Data Labeling
• AI Evaluation
• Large Language Models
• Prompt Engineering
• AI Training
• Software Engineering
• Technical Writing
• Analytical Thinking
• Decision-Making

Job areas

• Technology
• Software
• Data & Analytics
• Engineering
• Science & Research

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