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 make decisions? We're looking for Senior Machine Learning Engineers to author the reasoning traces that teach large language models how to think — step by step, decision by decision.
This is a fully remote, flexible contract role for senior-level engineers who understand model behavior at a deep level and can translate complex problem-solving into clear, structured, high-fidelity documentation. Your work won't just describe intelligence — it will create it.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
Author complex, high-fidelity reasoning traces for sophisticated real-world technical tasks
Document step-by-step planning, tool use, and decision-making in a clear and structured format
Design data strategies that help LLMs navigate intricate, multi-step problem-solving scenarios
Review and mentor trace quality to ensure optimal planning and tool-use documentation
Collaborate with AI research teams to set and maintain quality standards for reasoning data
Work independently and asynchronously — fully on your own schedule
Who You Are
Significant hands-on experience in Machine Learning, AI research, or closely related technical fields
Deep understanding of LLM reasoning, planning, and decision-making processes
Proven ability to decompose complex problems into clear, logical, well-documented steps
Experienced with advanced LLM evaluation, fine-tuning, or training methodologies
Strong written communication skills — you can explain intricate technical thinking clearly and precisely
Self-motivated and consistent when working independently
Nice to Have
Prior experience with data annotation, data quality assurance, or model evaluation pipelines
Top-tier Kaggle competition results (Grandmaster or Master level), demonstrating elite-level understanding of model performance and feature engineering
Background in AI safety, interpretability research, or RLHF workflows
Familiarity with agentic frameworks, tool-use models, or chain-of-thought prompting
Why Join Us
Work directly with world-leading AI research labs on frontier model development
Fully remote and flexible — work when and where it suits you
Freelance autonomy with the structure and purpose of meaningful, high-impact work
Get rare, hands-on exposure to how cutting-edge LLMs are trained and evaluated
Contribute to work that shapes how AI reasons — at a foundational level
Potential for ongoing work and contract extension as new projects launch

Work arrangement
Yes