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Senior Machine Learning Engineer

  • Canada
  • Remote
  • Posted Oct 8, 2026
  • 1 position

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Employment type
Contract
Experience level
Senior · 5+ years
Posting language
English
Working hours
40 hours per week
Seniority
Mid-Senior level

Job summary

Author and review high-fidelity reasoning traces that show how language models should plan, use tools, and make decisions. Develop and document data strategies and contribute training data to improve the reasoning and actions of advanced AI models.

Job details

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

What you’ll do

Author and review high-fidelity reasoning traces that show how language models should plan, use tools, and make decisions. Develop and document data strategies and contribute training data to improve the reasoning and actions of advanced AI models.

Requirements

Candidates should have substantial hands-on experience in machine learning, deep learning, or a related technical field, and be able to break complex problems into precise, structured reasoning steps. Familiarity with LLM evaluation, training pipelines, or model behavior analysis is expected, along with rigor, attention to detail, and the ability to work independently.

Benefits

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

Listed skills

  • Machine learning · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

  • Machine Learning
  • Deep Learning
  • Large Language Models
  • Reasoning Trace Authoring
  • Problem Decomposition
  • LLM Evaluation
  • Training Pipelines
  • Model Behavior Analysis
  • Data Strategy
  • Data Annotation
  • Data Quality Assurance
  • Reinforcement Learning
  • Chain-of-Thought Prompting
  • Agent-Based AI
  • LLM Fine-Tuning
  • RLHF

Job areas

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

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