Software Engineer – Machine Learning (AI Training)

Job summary

Review and evaluate AI-generated machine learning code for correctness, efficiency, and clarity. Develop high-quality ML solutions and provide clear explanations for model architecture and logic.

Job details

About The Role What if your machine learning expertise could directly influence how the most advanced AI systems in the world think, reason, and write code? We're looking for experienced ML engineers in Toronto to evaluate AI-generated machine learning solutions — catching errors, improving quality, and helping frontier AI models get genuinely better at one of the hardest things they do. This is a fully remote, flexible contract role. Work asynchronously on your own schedule. No fixed hours, no meetings — just high-impact, expert work that matters. Organization: Alignerr Type: Hourly Contract Location: Remote (Canada-based) Commitment: Flexible, project-based What You'll Do 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 Who You Are Deeply fluent in machine learning — you know your way around model development, data preprocessing, training pipelines, and deployment Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn Strong written communicator — able to explain complex ML concepts clearly and precisely Detail-oriented and rigorous — you catch what others miss and care about getting things right Self-motivated and comfortable working independently in an async environment Nice to Have 3–5+ years working on machine learning projects, pipelines, or MLOps Experience with model evaluation, cloud deployment, or production ML systems Bachelor's, Master's, or PhD in Computer Science, Machine Learning, or a related field Background in data labeling, RLHF, or other AI training workflows Prior experience with code review or technical writing Why Join Us Work on cutting-edge AI projects alongside leading research labs and top AI teams Fully remote and async — work when and where it suits you, with no minimum hour commitments beyond project needs Freelance autonomy with the structure of meaningful, task-based work Your contributions directly improve AI models used by top research labs and enterprise teams worldwide High-performing contributors take on expanded responsibilities and lead new programs Potential for ongoing work and contract extension as new projects launch

What you’ll do

Review and evaluate AI-generated machine learning code for correctness, efficiency, and clarity. Develop high-quality ML solutions and provide clear explanations for model architecture and logic.

Requirements

Requires deep fluency in machine learning frameworks like TensorFlow or PyTorch and strong written communication skills. Candidates should have experience with model development, data preprocessing, and independent async work.

Listed skills

• Machine learning · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Python
• TensorFlow
• PyTorch
• Scikit-learn
• Model Development
• Data Preprocessing
• Training Pipelines
• Deployment
• MLOps
• Technical Writing
• Code Review
• Data Labeling
• RLHF

Job areas

• Software
• Engineering
• Data & Analytics
• Technology
• Science & Research