Senior Machine Learning Engineer

Senior Machine Learning Engineer (AI Training) About The Role What if your deep expertise in machine learning could directly determine how the next generation of AI models 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 decision paths that teach LLMs how to think like experts. This isn't prompt engineering or model fine-tuning from the sidelines. This is foundational work: you'll be crafting the cognitive blueprints that shape how frontier AI models approach real-world technical challenges. Your output becomes training data that makes AI smarter, more reliable, and more capable. 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 for sophisticated technical tasks — showing exactly how a senior engineer would plan, reason, and act Document step-by-step decision-making processes including tool selection, problem decomposition, and validation logic Design structured traces that capture planning, tool use, and multi-step reasoning for real-world ML scenarios Review and mentor trace quality to ensure consistency, logical rigor, and optimal documentation of model decision paths Develop data strategies that help LLMs navigate intricate, ambiguous, and multi-constraint problems Contribute to the broader project mission: making AI reasoning more reliable and trustworthy at scale Who You Are Experienced in machine learning, AI systems, or a closely related technical field — you've worked with models, not just read about them Skilled at decomposing hard problems into clear, logical, well-documented steps — you can show your work Familiar with LLM evaluation, training methodologies, or RLHF-adjacent workflows Comfortable working independently and asynchronously — you're self-directed and produce consistent quality without hand-holding A precise, structured thinker who naturally documents reasoning rather than jumping to conclusions Nice to Have Prior experience with data annotation, data quality assurance, or AI evaluation pipelines Top-tier Kaggle competition results (Grandmaster or Master level) — a strong signal of model intuition and technical depth Hands-on experience with tool-use frameworks, agent-based reasoning, or chain-of-thought prompting Background in research engineering, applied ML, or technical AI safety Why Join Us Work directly with teams building cutting-edge AI at leading research labs and frontier model companies Fully remote and async — work when and where you're most productive Freelance autonomy with the intellectual depth of senior-level technical work Rare opportunity to influence how advanced AI models reason from the ground up Exposure to the inner workings of LLM training and evaluation at the highest level Potential for ongoing work and contract extension as new projects launch

Author high-fidelity reasoning traces and structured decision paths to train frontier AI models. Develop data strategies and review trace quality to improve the reliability and trustworthiness of AI reasoning.

Requires deep experience in machine learning and AI systems with a proven ability to decompose complex technical problems into logical steps. Candidates should be familiar with LLM training methodologies and comfortable working independently in an asynchronous environment.

• Machine learningPreferred

Identified from the job description. Confirm important requirements above.

• Machine Learning
• AI Systems
• Reasoning Traces
• LLM Evaluation
• RLHF
• Problem Decomposition
• Data Annotation
• Chain-of-Thought Prompting
• Agent-Based Reasoning
• Technical Documentation
• Data Quality Assurance
• AI Safety

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

Minimum experience

5+ years

Apply by

Sep 6, 2026

Posting language

English

Working hours

40 hours per week

Location requirements

Country, Vancouver, British Columbia, Canada

Seniority

Mid-Senior level