Senior Machine Learning Engineer

Senior Machine Learning Engineer (AI Training) About The Role What if your deep expertise in machine learning could directly influence how the next generation of AI systems reason, plan, and solve complex problems? We're looking for Senior Machine Learning Engineers to author high-fidelity reasoning traces — the structured, step-by-step thinking records that teach AI models how to navigate real-world tasks with precision and reliability. This isn't prompt engineering or basic annotation. This is senior-level, intellectually demanding work that puts your architectural knowledge and ML intuition at the center of how tomorrow's AI thinks. Fully remote. Flexible hours. Meaningful impact. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Author complex, high-fidelity reasoning traces that capture how an LLM should plan, use tools, and make decisions step by step Break down sophisticated technical problems into clear, logical, well-documented reasoning chains Design and document data strategies that help LLMs navigate intricate real-world scenarios Review and provide expert feedback on traces to ensure optimal planning and decision-making quality Contribute directly to training data that improves how frontier AI models reason and act Who You Are Experienced ML practitioner with significant hands-on expertise in machine learning, deep learning, or a closely related technical field Skilled at decomposing complex problems into structured, traceable reasoning steps Familiar with LLM evaluation methodologies, training pipelines, or model behavior analysis Detail-oriented and rigorous — you care about precision in both logic and documentation Self-directed and comfortable working independently in an asynchronous environment Nice to Have Prior experience with data annotation, data quality assurance, or AI evaluation systems Top-tier Kaggle competition results (Grandmaster or Master level) — a strong signal of deep model understanding and performance optimization instincts Background in reinforcement learning, chain-of-thought prompting, or agent-based AI frameworks Experience contributing to LLM fine-tuning or RLHF workflows Why Join Us Work alongside world-leading AI research teams and labs on frontier model development Fully remote and asynchronous — work on your schedule, from anywhere Freelance autonomy with intellectually stimulating, high-impact work Direct, meaningful contribution to how advanced AI systems learn to reason Potential for ongoing work and contract extension as new projects launch

Author high-fidelity reasoning traces to teach AI models how to plan and solve complex problems. Design data strategies and provide expert feedback to improve the reasoning and decision-making quality of frontier AI models.

Requires an experienced ML practitioner skilled in decomposing complex problems into structured reasoning steps. Familiarity with LLM training pipelines and evaluation methodologies is essential.

• Machine learningPreferred

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Deep Learning
• LLM Evaluation
• Reasoning Traces
• Data Strategy
• Model Behavior Analysis
• Reinforcement Learning
• Chain-of-Thought Prompting
• Agent-based AI Frameworks
• RLHF
• LLM Fine-tuning
• Technical Documentation

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

Minimum experience

5+ years

Posting language

English

Working hours

40 hours per week

Seniority

Mid-Senior level