Alignerr

Senior Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer on a flexible hourly contract (10–40 hours/week) with a pay rate of "unknown," fully remote. Key skills include model reasoning, LLM behavior understanding, and problem decomposition. Prior experience in data annotation or RLHF is a plus.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
640
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🗓️ - Date
April 30, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London, England, United Kingdom
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🧠 - Skills detailed
#Data Quality #Model Evaluation #AI (Artificial Intelligence) #Quality Assurance #ML (Machine Learning)
Role description
Senior Machine Learning Engineer (AI Training) About The Role What if your deep expertise in machine learning could directly shape how the world's most advanced AI systems reason, plan, and make decisions? We're looking for Senior Machine Learning Engineers to author high-fidelity reasoning traces — the structured, step-by-step thought processes that teach LLMs how to solve real-world problems reliably. This isn't prompt engineering or data entry. This is senior-level intellectual work: designing the cognitive scaffolding that makes AI smarter, more trustworthy, and more capable in production environments. This is a fully remote, flexible contract role built for experienced ML professionals who want to work at the frontier of AI development. • 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 reach decisions for sophisticated technical tasks • Design structured traces that capture multi-step problem decomposition, intermediate reasoning, and decision logic with clarity and precision • Review and refine traces to ensure consistency, logical soundness, and alignment with LLM training objectives • Develop data strategies that help models navigate ambiguous, multi-constraint, real-world scenarios • Contribute architectural insight to trace design — not just what the model should do, but why and how it should reason through it Who You Are • Experienced ML practitioner with a strong grasp of model reasoning, evaluation, and training dynamics • Skilled at decomposing complex technical problems into clear, logical, well-documented steps • Familiar with LLM behavior — you understand how models fail and what high-quality training data looks like • Detail-oriented and rigorous — you hold yourself to a high bar for clarity and correctness • Self-directed and comfortable producing high-quality work independently Nice to Have • Prior experience with data annotation, data quality assurance, or model evaluation pipelines • Background in RLHF, chain-of-thought prompting, or reasoning-focused ML research • Top-tier Kaggle competition results (Grandmaster or Master level) demonstrating elite-level model intuition and problem-solving • Experience building or evaluating agentic AI systems with tool use and multi-step planning Why Join Us • Work directly with leading AI research labs on some of the most technically challenging problems in the field • Fully remote and async-friendly — work when and where it suits you • Freelance autonomy with the intellectual depth of frontier AI work • Gain rare, hands-on exposure to how cutting-edge LLMs are trained and evaluated • Potential for ongoing contract extension as new projects launch