Senior Machine Learning Engineer

Senior Machine Learning Engineer

What if your deep expertise in machine learning could directly shape how the next generation of AI models think, plan, and make decisions? We're looking for Senior Machine Learning Engineers to author high-fidelity reasoning traces — structured, step-by-step records of how an AI should approach and solve complex real-world problems.

This isn't model training in the traditional sense. You'll be working at the frontier of AI development, capturing the reasoning process itself — the planning, tool use, and decision-making logic that teaches large language models to behave reliably in the wild.

This is a fully remote, flexible contract role designed for senior practitioners who want meaningful, intellectually stimulating work on their own schedule.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Author complex, high-fidelity reasoning traces that document how an LLM should plan, use tools, and arrive at decisions for sophisticated technical tasks
• Design and implement data strategies that help AI models navigate intricate, real-world scenarios reliably
• Review and mentor structured traces produced by others — ensuring rigorous documentation of planning steps and tool-use logic
• Decompose multi-step technical problems into clear, logical, and reproducible decision paths
• Collaborate with a globally distributed team working at the cutting edge of AI alignment and model training

Who You Are

• Experienced machine learning practitioner with significant hands-on exposure to model reasoning, evaluation, or training methodologies
• Skilled at breaking down complex, ambiguous problems into structured, step-by-step logic
• Familiar with how large language models work — their strengths, failure modes, and how training data shapes their behavior
• Detail-oriented and precise in how you document technical processes
• Self-directed and comfortable working independently in an async, remote environment

Nice to Have

• Prior experience in data annotation, data quality assurance, or AI evaluation systems
• Top-tier Kaggle competition results (e.g., Grandmaster or Master level) — a strong signal of deep model intuition and feature engineering expertise
• Experience contributing to LLM fine-tuning, RLHF pipelines, or related alignment workflows
• Background in technical writing, research, or structured documentation

Why Join Us

• Work directly with teams building some of the most advanced AI models in the world
• Fully remote and async — work when and where it suits you, with 10–40 hours of weekly flexibility
• Freelance autonomy paired with intellectually meaningful, high-impact work
• Gain rare, hands-on exposure to how frontier LLMs are trained to reason at scale
• Potential for ongoing work and contract extension as new projects launch