Machine Learning Engineer

Alignerr Corp.; Oxford; À distance; GBP 55 000 - 83 000; Plein temps

Avantages offerts par ce poste

Fully remote

Flexible hours

Freelance autonomy

Résumé du poste

Alignerr is seeking a Machine Learning Engineer (AI Data Trainer) to help shape how AI systems reason, plan, and solve real-world problems. This is a fully remote, hourly contract role with flexible 10–40 hours per week.

You will author structured reasoning traces, map step-by-step decision processes, and create high-quality training data to improve model reliability. You will work independently, communicating precisely with minimal supervision.

Qualifications

• Background in Machine Learning, Computer Science, or a closely related technical field.
• Able to articulate complex logical and technical reasoning in clear, structured writing.
• Strong analytical thinker who can identify gaps or errors in AI decision-making workflows.

Responsabilités

• Author clear, structured reasoning traces that document how an AI should plan and execute complex technical tasks.
• Map out step-by-step decision-making processes — including tool use, logic branching, and problem-solving strategies.
• Create high-quality training data that demonstrates reliable, grounded reasoning in real-world scenarios.
• Evaluate and refine AI outputs to improve the quality and consistency of model decision-making.
• Work independently and asynchronously — fully on your own schedule.

Connaissances

Machine Learning

Technical writing

Analytical thinking

Independent worker

Formation

CS/CS-related degree

Outils

LLM architectures

Prompt engineering

Description du poste

Machine Learning Engineer (AI Data Trainer)

About The Role

What if your 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 Machine Learning Engineers to work at the frontier of AI development — capturing the step-by-step reasoning and decision-making processes that teach large language models to think more reliably.

This is a fully remote, flexible contract role built for technical minds who can break down complex logic and communicate it with precision. You won't just observe how AI is trained — you'll be a core part of making it smarter.

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

What You'll Do

• Author clear, structured reasoning traces that document how an AI should plan and execute complex technical tasks
• Map out step-by-step decision-making processes — including tool use, logic branching, and problem-solving strategies
• Create high-quality training data that demonstrates reliable, grounded reasoning in real-world scenarios
• Evaluate and refine AI outputs to improve the quality and consistency of model decision-making
• Work independently and asynchronously — fully on your own schedule

Who You Are

• Background in Machine Learning, Computer Science, or a closely related technical field
• Able to articulate complex logical and technical reasoning in clear, structured writing
• Strong analytical thinker who can identify gaps or errors in AI decision-making workflows
• Detail-oriented and consistent — you take pride in producing high-quality, precise work
• Self-motivated and comfortable working independently without close supervision

Nice to Have

• Prior experience with data annotation, data quality assurance, or AI evaluation systems
• Familiarity with LLM architectures, prompt engineering, or RLHF workflows
• Background in software engineering, applied research, or technical writing
• Experience working with structured reasoning frameworks or chain-of-thought methodologies

Why Join Us

• Work directly on cutting-edge AI projects alongside leading research labs and AI teams
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure of meaningful, impactful technical work
• Get rare, hands-on exposure to how advanced LLMs are actually trained and improved
• Contribute to AI development that shapes how models reason across millions of real-world use cases
• Potential for ongoing work and contract extension as new projects launch