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

Work arrangement
Yes