About the Role
What if your deep expertise in machine learning could directly shape how the next generation of AI systems reason, plan, and solve real-world problems? We're looking for Senior Machine Learning Experts to author high-fidelity reasoning traces — structured, step-by-step records of how an AI should think through complex tasks — that train large language models to reason more reliably and effectively.
This is a fully remote, flexible contract role built for senior ML professionals who want meaningful, intellectually stimulating work on the cutting edge of AI development. No office. No fixed hours. Just high-impact work at the frontier of AI.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Author complex, high-fidelity reasoning traces that capture how an LLM should plan, use tools, and make decisions across sophisticated technical tasks
- Break down intricate real-world problems into clear, logical, well-documented steps that serve as training data for frontier AI models
- Review and provide expert-level feedback on reasoning traces produced by other contributors to ensure quality and consistency
- Design data strategies that help LLMs navigate multi-step decision-making scenarios more reliably
- Apply your knowledge of advanced ML architectures and model behavior to produce traces that reflect genuine expert reasoning
- Work independently and asynchronously — fully on your own schedule
Who You Are
- Experienced machine learning practitioner with deep expertise in model reasoning, architecture, and evaluation
- Able to decompose complex, ambiguous problems into clear, logical, and well-documented workflows
- Comfortable working with advanced LLM evaluation and training methodologies
- Naturally rigorous and detail-oriented — you care about getting the reasoning right, not just the answer
- Strong written communicator who can articulate technical thinking in a clear, structured way
- Self-directed and reliable when working independently without supervision
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 elite-level understanding of model performance and feature engineering
- Background in AI safety, alignment research, or RLHF-adjacent workflows
- Experience writing technical documentation, research notes, or structured decision logs
Why Join Us
- Work directly with leading AI research labs and teams building frontier models
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-impact technical work
- Contribute to AI development that shapes how the world's most advanced models reason and act
- Potential for ongoing work and contract extension as new projects launch