Machine Learning Engineer
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IT/Tech
AI Evaluation, AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Data Annotation/ AI Labeling
Job Description & How to Apply Below
The Role
What if your deep technical expertise could directly shape how the world's most advanced AI systems reason through complex problems? We're looking for Machine Learning Engineers to help train cutting-edge AI models — not by writing model code, but by demonstrating the kind of expert, structured thinking that makes AI genuinely reliable in the real world.
Machine Learning Engineer (AI Training) AboutThe Role
What if your deep technical expertise could directly shape how the world's most advanced AI systems reason through complex problems? We're looking for Machine Learning Engineers to help train cutting-edge AI models — not by writing model code, but by demonstrating the kind of expert, structured thinking that makes AI genuinely reliable in the real world.
This is a fully remote, flexible contract role. You'll work with Alignerr, a team partnered with leading AI research labs, to produce high-quality reasoning traces and decision-making workflows that teach AI how to solve sophisticated technical challenges — step by step, tool by tool.
- Organization:
Alignerr - Type:
Hourly Contract - Location:
Remote - Commitment: 10–40 hours/week
- Construct precise, well-structured logical workflows that demonstrate expert reasoning for complex ML and engineering problems
- Document sequential decision-making processes — how a skilled engineer strategizes, selects tools, and adapts when things go wrong
- Generate rich training datasets that show AI models what proficient, real-world problem-solving actually looks like
- Review and critically evaluate AI-generated reasoning steps, identifying gaps, errors, and areas for improvement
- Work independently and asynchronously — on your own schedule, at your own pace
- Professional background in Machine Learning, Software Engineering, or a related technical discipline
- Exceptional ability to articulate complex reasoning processes in a clear, structured, and reproducible way
- Strong critical thinking skills — you can spot flawed logic and know how to correct it
- Comfortable working with technical tools and documenting their use systematically
- Advanced degree (Master's or PhD) in a relevant field
- Prior experience with data annotation, data labeling, or AI evaluation pipelines
- Familiarity with LLM capabilities, limitations, and training methodologies
- Background in technical writing, research documentation, or knowledge engineering
- Experience working across multiple ML domains — NLP, computer vision, reinforcement learning, etc.
- Work directly on projects with leading AI research labs pushing the frontier of what LLMs can do
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, intellectually stimulating work
- Gain rare behind-the-scenes insight into how frontier AI models are trained and improved
- Contribute to work that makes AI more reliable, capable, and trustworthy at scale
- Potential for ongoing work and contract extension as new projects launch
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