Machine Learning Researcher and Task Reviewer

You will create, solve, review, and validate machine learning engineering tasks against defined correctness and performance requirements. The work covers model development, training and inference systems, numerical computing, performance optimization, and Python.

You will also build reproducible workflows, investigate numerical or system-level failures, improve memory use or throughput, and check that implementations meet objective requirements.

• Develop and validate models, training pipelines, inference systems, and evaluation systems.
• Implement model components, data pipelines, numerical methods, and supporting infrastructure.
• Use Python and command-line tools to create reproducible workflows.
• Review coding-intensive machine learning, systems, and numerical-computing solutions.

• Pay: $60 to $120 per hour equivalent, paid per task that meets the project specifications.
• Schedule: Approximately 15 hours per week with flexible scheduling.
• Work arrangement: Fully remote contractor opportunity.
• Location: Open to candidates in the listed countries across the Americas, Europe, Asia, Africa, and the Middle East.
• Language: Professional fluency in English.
• Education: A master's degree or PhD in computer science, machine learning, artificial intelligence, applied mathematics, statistics, engineering, or a closely related quantitative discipline is required.
• Experience: Strong professional or research experience in machine learning and practical proficiency with Python and coding agents.
• You should be able to handle coding-intensive model, systems, and numerical-computing problems.
• Helpful tools include PyTorch, JAX, NumPy, SciPy, SGLang, vLLM, llama.cpp, tokenizers, and transformers.
• Experience in a technology company, AI laboratory, research organization, or recognized engineering environment is preferred. Exceptional open-source or academic experience may also qualify.

You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.

AI training work uses human judgment to prepare and evaluate the examples, code, and model outputs that help artificial intelligence systems improve. Specialized contributors are paid for applying technical expertise to difficult tasks such as model evaluation, software testing, numerical analysis, and performance review.