Machine Learning Engineer

Job summary

Create structured reasoning logs and reproducible workflows that demonstrate expert technical problem-solving, including how tools are selected and evaluated. Generate training datasets and audit AI-generated reasoning traces for logical consistency and technical accuracy.

Job details

Machine Learning Engineer (AI Data Trainer) About The Role What if your deep technical expertise could directly shape how the next generation of AI models reason, plan, and solve real-world problems? We're looking for Machine Learning Engineers to help train and improve large language models by demonstrating how expert-level thinking actually works — step by step, tool by tool, decision by decision. This is a fully remote, flexible contract role designed for experienced technical professionals who know how to break down complex problems and explain their reasoning with precision. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Construct detailed, structured reasoning logs that walk through how sophisticated technical problems are approached and solved Document sequential decision-making workflows — capturing how tools are selected, applied, and evaluated at each step Generate high-quality training datasets that demonstrate proficient, expert-level problem-solving for AI models Audit and refine AI-generated reasoning traces to ensure logical consistency and technical accuracy Translate complex methodologies into clearly articulated, reproducible workflows Who You Are Professionally experienced in Machine Learning, Software Engineering, or a related technical discipline Exceptionally clear at explaining intricate technical processes — you can make complex reasoning legible A rigorous critical thinker who can identify gaps, errors, or inefficiencies in AI-generated reasoning Comfortable working independently and asynchronously on task-based assignments Holds or is pursuing a Master's Degree or PhD in a relevant field Nice to Have Prior experience with data annotation, data quality assurance, or AI evaluation systems Familiarity with LLM behavior, prompt engineering, or model evaluation methodologies Background in technical writing, research documentation, or structured problem-solving frameworks Experience working across multiple ML domains — NLP, computer vision, reinforcement learning, etc. Why Join Us Work directly with leading AI research labs on projects at the frontier of model development Fully remote and async — work when and where it suits you, with no fixed hours Freelance autonomy with meaningful, intellectually engaging work Gain rare, hands-on insight into how cutting-edge LLMs are trained and improved Potential for ongoing work and contract extension as new projects launch

What you’ll do

Create structured reasoning logs and reproducible workflows that demonstrate expert technical problem-solving, including how tools are selected and evaluated. Generate training datasets and audit AI-generated reasoning traces for logical consistency and technical accuracy.

Requirements

Candidates should have professional experience in machine learning, software engineering, or a related technical field, and be able to explain complex technical processes clearly and critically. A master's degree or PhD in a relevant field is held or in progress; experience with data annotation, AI evaluation, LLMs, or technical documentation is an advantage.

Benefits

• Flexible Schedule
• Fully Remote Work
• Freelance Autonomy
• Potential for Ongoing Work and Contract Extension

Listed skills

• Machine learning · Preferred
• prompt engineering · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Software Engineering
• Large Language Models
• Technical Problem-Solving
• Structured Reasoning
• Decision-Making Workflows
• Training Data Generation
• Data Annotation
• Data Quality Assurance
• AI Evaluation
• Prompt Engineering
• Model Evaluation
• Technical Writing
• Natural Language Processing
• Computer Vision
• Reinforcement Learning

Job areas

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

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