About the Role
What if your deep expertise in machine learning could directly determine how the next generation of AI reasons through complex, real-world problems? We're looking for Senior Machine Learning Engineers to author high-fidelity reasoning traces — the structured, step-by-step decision paths that teach large language models how to plan, use tools, and think reliably.
This is a fully remote, flexible contract role built for experienced ML practitioners who want to work at the frontier of AI development. Your architectural insights and problem-decomposition skills won't just support a product — they'll shape how AI thinks.
- 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, reason, and act across sophisticated technical tasks
- Design structured traces that clearly document tool use, decision-making logic, and multi-step planning
- Apply senior-level architectural thinking to ensure traces reflect reliable, real-world problem-solving approaches
- Review and mentor the quality of reasoning documentation to uphold rigorous standards
- Develop data strategies that help LLMs navigate intricate, ambiguous scenarios with greater reliability
- Work independently and asynchronously on your own schedule
Who You Are
- Significant hands-on experience in Machine Learning, AI research, or a closely related technical field
- Demonstrated ability to decompose complex, multi-step problems into clear, logical, and well-documented processes
- Deep familiarity with LLM evaluation, training methodologies, and model reasoning patterns
- Strong written communicator — you can translate sophisticated technical thinking into structured, readable documentation
- Self-directed and rigorous, with a high bar for quality
Nice to Have
- Prior experience with data annotation pipelines, data quality frameworks, or AI evaluation systems
- Top-tier Kaggle competition results (Grandmaster or Master level), demonstrating elite-level model performance expertise
- Background in AI safety, RLHF, or human feedback integration workflows
- Experience designing or auditing training data at scale
Why Join Us
- Work directly with world-leading AI research labs on genuinely cutting-edge projects
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy paired with meaningful, high-impact technical work
- Gain rare, deep exposure to how frontier LLMs are trained and evaluated
- Be part of a global community of expert contributors shaping the future of AI
- Potential for ongoing work and contract extension as new projects launch