Senior Machine Learning Expert
- Vancouver, British Columbia, Canada
- Remote
- Posted Oct 8, 2026
- 1 position
US$60–US$80 / hour
Opens LinkedIn
- Employment type
- Contract
- Experience level
- Senior · 5+ years
- Posting language
- English
- Working hours
- 40 hours per week
- Location requirements
- Country, Vancouver, British Columbia, Canada
- Seniority
- Mid-Senior level
Job summary
Author and review structured, high-fidelity reasoning traces that teach large language models to plan, use tools, and solve complex technical problems. Develop data strategies for multi-step decision-making and provide expert feedback to ensure training data is clear, rigorous, and consistent.
Job details
Senior Machine Learning Expert (AI Training) About The Role What if your deep expertise in machine learning could directly shape how the next generation of AI systems reason, plan, and solve real-world problems? We're looking for Senior Machine Learning Experts to author high-fidelity reasoning traces — structured, step-by-step records of how an AI should think through complex tasks — that train large language models to reason more reliably and effectively. This is a fully remote, flexible contract role built for senior ML professionals who want meaningful, intellectually stimulating work on the cutting edge of AI development. No office. No fixed hours. Just high-impact work at the frontier of AI. 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 across sophisticated technical tasks Break down intricate real-world problems into clear, logical, well-documented steps that serve as training data for frontier AI models Review and provide expert-level feedback on reasoning traces produced by other contributors to ensure quality and consistency Design data strategies that help LLMs navigate multi-step decision-making scenarios more reliably Apply your knowledge of advanced ML architectures and model behavior to produce traces that reflect genuine expert reasoning Work independently and asynchronously — fully on your own schedule Who You Are Experienced machine learning practitioner with deep expertise in model reasoning, architecture, and evaluation Able to decompose complex, ambiguous problems into clear, logical, and well-documented workflows Comfortable working with advanced LLM evaluation and training methodologies Naturally rigorous and detail-oriented — you care about getting the reasoning right, not just the answer Strong written communicator who can articulate technical thinking in a clear, structured way Self-directed and reliable when working independently without supervision Nice to Have Prior experience with data annotation, data quality assurance, or model evaluation systems Top-tier Kaggle competition results (Grandmaster or Master level) demonstrating elite-level understanding of model performance and feature engineering Background in AI safety, alignment research, or RLHF-adjacent workflows Experience writing technical documentation, research notes, or structured decision logs Why Join Us Work directly with leading AI research labs and teams building frontier models Fully remote and flexible — work when and where it suits you Freelance autonomy with the structure of meaningful, high-impact technical work Contribute to AI development that shapes how the world's most advanced models reason and act Potential for ongoing work and contract extension as new projects launch
What you’ll do
Author and review structured, high-fidelity reasoning traces that teach large language models to plan, use tools, and solve complex technical problems. Develop data strategies for multi-step decision-making and provide expert feedback to ensure training data is clear, rigorous, and consistent.
Requirements
Requires deep machine learning expertise, including knowledge of model reasoning, architecture, evaluation, and advanced LLM training methodologies. Candidates should be rigorous, detail-oriented, strong technical communicators, and able to work independently; prior annotation, evaluation, AI safety, alignment, or RLHF experience is advantageous.
Benefits
- Fully Remote Work
- Flexible Schedule
- 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
- Large Language Models
- Model Reasoning
- Machine Learning Architecture
- Model Evaluation
- AI Training
- Reasoning Trace Authoring
- Problem Decomposition
- Data Strategy
- Data Annotation
- Data Quality Assurance
- Feature Engineering
- AI Safety
- AI Alignment
- Reinforcement Learning from Human Feedback
- Technical Writing
Job areas
- Technology
- Data & Analytics
- Software
- Science & Research
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