Senior Machine Learning Engineer

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 systems reason, plan, and make decisions? We're looking for Senior Machine Learning Engineers to author the high-fidelity reasoning traces that teach large language models how to think - step by step, decision by decision.

This isn't prompt engineering or routine annotation. This is senior-level intellectual work: designing structured traces that capture real planning, tool use, and problem decomposition for complex technical tasks. The data you create will directly influence how reliably AI models reason in the real world.

This is a fully remote, flexible contract role built for experienced ML practitioners who want to contribute to something that genuinely matters.

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

What You'll Do

• Author complex, high-fidelity reasoning traces that show how an LLM should plan, use tools, and make decisions to solve sophisticated technical tasks
• Apply senior-level architectural insight to ensure traces reflect sound, reliable model decision-making
• Decompose intricate real-world problems into clear, logical, and well-documented steps
• Review and mentor structured traces to maintain the highest standards of planning and tool-use documentation
• Design data strategies that help LLMs navigate multi-step, ambiguous, and high-stakes scenarios
• Contribute to training pipelines that push the frontier of what AI can reason through

Who You Are

• Experienced in Machine Learning or a closely related technical field, with a strong focus on model reasoning and decision-making
• Skilled at breaking down complex problems into structured, logical, and clearly documented steps
• Familiar with advanced LLM evaluation and training methodologies
• Rigorous in your thinking - you care about correctness, nuance, and the downstream impact of training data quality
• Self-directed and comfortable working independently in an asynchronous remote environment

Nice to Have

• Prior experience with data annotation, data quality assurance, or model evaluation systems
• Top-tier Kaggle competition results (Grandmaster or Master level), demonstrating deep understanding of model performance and feature engineering
• Background in ML research, applied AI, or LLM fine-tuning workflows
• Experience designing or auditing training datasets for complex reasoning tasks

Why Join Us

• Work at the frontier of AI development alongside world-leading research labs and teams
• Fully remote and flexible - structure your hours around your life, not the other way around
• Freelance autonomy with the substance of genuinely impactful, intellectually challenging work
• Direct influence on how the next generation of AI models learn to reason and solve hard problems
• Potential for ongoing work and contract extension as new projects launch