MABASA / LINKEDIN
Senior Machine Learning Engineer
Alignerr
- Location
- Not specified
- Work type
- contract
- Source publication date
- Original publication date not confirmed
- Source closing date
- Not supplied — check original advert
Job description from the source
**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
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