Machine Learning Engineer

Alignerr; City of Melbourne; On-site; AUD 83,000 - 138,000; Part time

Job summary

Alignerr is seeking a Machine Learning Engineer to help train cutting-edge AI models by demonstrating how expert engineers think and reason. This fully remote, hourly contract role offers flexible hours (10–40 hours/week) and the chance to contribute to training data that teaches AI to reason and solve problems.

You will produce precise reasoning logs, document decision-making workflows, and create high-quality training datasets.

Qualifications

• Experience explaining complex technical reasoning clearly.
• Ability to document step-by-step decision-making workflows clearly.

Responsibilities

• Produce precise, well-structured reasoning logs for expert approaches to problems.
• Document step-by-step decision-making workflows including strategy and tool selection.
• Generate high-quality training datasets demonstrating proficient problem-solving for AI models.
• Audit and refine AI-generated reasoning chains to identify gaps or errors.
• Work across a range of ML and engineering scenarios, translating intuition into structured examples.

Skills

ML engineering

Technical writing

Structured problem-solving

Independent work

Education

Master's or PhD in ML/CS

Job description

Machine Learning Engineer (AI Data Trainer)

About The Role

What if your technical expertise could directly influence how the world's most advanced AI systems learn to reason, plan, and solve problems? We're looking for Machine Learning Engineers to help train cutting-edge large language models — not by writing model code, but by demonstrating how expert technical minds actually think.

Machine Learning Engineer (AI Data Trainer)

About The Role

What if your technical expertise could directly influence how the world's most advanced AI systems learn to reason, plan, and solve problems? We're looking for Machine Learning Engineers to help train cutting-edge large language models — not by writing model code, but by demonstrating how expert technical minds actually think.

This is a fully remote, flexible contract role built for experienced engineers and researchers who can articulate complex reasoning with precision. Your work will form the backbone of training data that teaches AI to think like a specialist.

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

What You'll Do

• Produce precise, well-structured reasoning logs that capture how expert engineers approach sophisticated technical problems
• Document step-by-step decision-making workflows — covering strategy, tool selection, and problem decomposition
• Generate high-quality training datasets that demonstrate proficient, reliable problem-solving for AI models
• Audit and refine AI-generated reasoning chains, identifying gaps, errors, or logical inconsistencies
• Work across a range of complex ML and engineering scenarios, translating expert intuition into structured, learnable examples

Who You Are

• Professional background in Machine Learning, Software Engineering, or a related technical discipline
• Exceptional ability to explain complex technical reasoning in a clear, organized, and reproducible way
• Strong critical thinking skills — you can evaluate the quality of a logical argument and know when something doesn't hold up
• Methodical and detail-oriented, with a consistent approach to structured problem-solving
• Comfortable working independently and managing your own time across flexible hours

Nice to Have

• Master's Degree or PhD in Machine Learning, Computer Science, or a related field
• Prior experience with data annotation, evaluation systems, or AI quality assurance
• Familiarity with LLM behavior, prompt engineering, or AI reasoning frameworks
• Background in technical writing, research documentation, or instructional design

Why Join Us

• Work directly with teams building some of the most advanced AI models in the world
• Fully remote and asynchronous — work on your own schedule, from anywhere
• Freelance autonomy with the structure of meaningful, high-impact technical work
• Gain rare, hands‑on exposure to how frontier LLMs are trained and evaluated
• Potential for ongoing work and contract extension as new projects launch