Software Engineer - Machine Learning

Software Engineer – Machine Learning (AI Training) 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 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, from wherever you are. No fixed hours, no meetings — just high-impact, expert work that matters. 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