Senior Machine Learning Engineer (NM+)
alignerr | 1 hours ago | Remote

  • Author complex, high-fidelity reasoning traces that capture planning, tool use, and multi-step decision-making for sophisticated technical tasks
  • Design and document structured traces that demonstrate how a model should reason through real-world scenarios — not just what the answer is, but how to get there
  • Review and quality-check traces produced by other contributors, ensuring clarity, logical soundness, and technical accuracy
  • Develop data strategies that help LLMs navigate ambiguous, multi-layered problems with reliable, consistent reasoning
  • Apply senior-level architectural insight to ensure traces reflect best practices in model decision-making and problem decomposition

Who You Are

  • Experienced in machine learning, AI research, or a closely related technical field — you understand how models learn and where they fail
  • Skilled at decomposing complex problems into clear, documented, logical steps that others can follow and evaluate
  • Familiar with LLM training pipelines, evaluation methodologies, and the mechanics of how models develop reasoning capabilities
  • A precise, structured thinker who can translate expertise into high-quality written documentation
  • Self-directed and reliable — you produce consistent, high-quality work without hand-holding

Nice to Have

  • Prior experience with data annotation, data quality assurance, or AI evaluation systems
  • Top-tier Kaggle competition results (Grandmaster or Master level) demonstrating elite-level model understanding and performance optimization
  • Background in reinforcement learning, chain-of-thought prompting, or agentic AI systems
  • Experience working with or evaluating frontier LLMs

Why Join Us

  • Work directly with some of the world's leading AI research teams and labs on cutting-edge model development
  • Fully remote and flexible — structure your work around your life, not the other way around
  • Freelance autonomy with meaningful, intellectually stimulating work on problems that actually matter
  • Gain deep, hands-on exposure to how frontier LLMs are trained and evaluated
  • Potential for ongoing work and contract extension as new projects launch
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