Senior Machine Learning Engineer

alignerr

Remote NM Years Exp Posted 70d ago

Job Description

  • Author complex, high-fidelity reasoning traces that document how an LLM should plan, use tools, and make decisions across sophisticated technical tasks
  • Design structured traces that capture multi-step problem decomposition, logical inference, and real-world decision-making strategies
  • Review and refine reasoning traces to ensure they reflect sound ML thinking and produce reliable, generalizable model behaviour
  • Develop data strategies that help LLMs navigate intricate, open-ended scenarios with greater consistency and accuracy
  • Contribute senior-level insights that elevate the overall quality and depth of training data

Who You Are

  • Experienced in machine learning, AI research, or a closely related technical field — you understand how models learn and where they go wrong
  • Skilled at breaking down complex problems into clear, logical, documented steps — the kind of thinking that makes great training data
  • Familiar with LLM evaluation, fine-tuning, or training methodologies
  • A precise, structured communicator who can make sophisticated reasoning legible and reproducible
  • Self-directed and comfortable producing high-quality work independently

Nice to Have

  • Prior experience with data annotation, evaluation systems, or AI quality assurance
  • Top-tier Kaggle competition results (Grandmaster or Master level) — a strong signal of your model intuition and problem-solving depth
  • Hands-on experience working with or evaluating large language models directly
  • Background in AI safety, interpretability, or model alignment research

Why Join Us

  • Work at the frontier — collaborate with world-leading AI research labs on projects that are shaping the future of machine intelligence
  • Fully remote and flexible — work when and where you do your best thinking
  • Freelance autonomy with the substance of genuinely meaningful, high-impact work
  • Go beyond typical ML contracting — your expertise directly influences how frontier models reason and behave
  • Potential for ongoing work and contract extension as new projects launch

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