Remote ML Engineer: AI Training & Code Review

Alignerr Corp.; Sydney; Remote; AUD 83,000 - 165,000; Part time

Job summary

Alignerr is seeking experienced ML engineers in Sydney and across Australia to evaluate AI-generated machine learning solutions and catch errors, improving quality for frontier AI models. This is a fully remote, flexible hourly contract with asynchronous work and no fixed hours.

You will operate independently on high-impact tasks that matter to advancing AI capabilities. You will review Python-based ML code, write high-quality ML solutions, and craft clear explanations of model decisions.

Qualifications

• 3–5+ years working on machine learning projects, pipelines, or MLOps.
• Experience with model evaluation, cloud deployment, or production ML systems.
• Background in data labeling, RLHF, or other AI training workflows.

Responsibilities

• Review and evaluate AI-generated machine learning code - including Python, TensorFlow, PyTorch, and scikit-learn - for correctness, efficiency, scalability, and clarity
• Write high-quality ML solutions to modeling, data processing, and deployment problems across a range of difficulty levels
• Craft clear, developer-friendly explanations for model architecture decisions, code logic, and problem-solving approaches
• Identify edge cases, ambiguities, and weaknesses in problem statements, datasets, or AI-generated responses
• Help set the quality bar for how AI understands and produces machine learning code

Skills

Machine learning

TensorFlow

PyTorch

scikit-learn

Strong written communication

Education

Bachelor's degree in Computer Science/ML or related field

Master's degree

PhD

Tools

TensorFlow

PyTorch

scikit-learn

Job description

Alignerr is seeking experienced ML engineers in Sydney and across Australia to evaluate AI-generated machine learning solutions and catch errors, improving quality for frontier AI models. This is a fully remote, flexible hourly contract with asynchronous work and no fixed hours.

You will operate independently on high-impact tasks that matter to advancing AI capabilities. You will review Python-based ML code, write high-quality ML solutions, and craft clear explanations of model decisions.