Senior Machine Learning Engineer (English, MSc or PhD)

You will create, solve, review, and validate challenging machine learning engineering tasks for AI training. The work combines model development, training and inference systems, numerical computing, performance optimization, reproducible workflows, and objective correctness checks.

• Implement or modify machine learning model components.
• Build training and inference workflows, data pipelines, and evaluation systems.
• Use Python and command-line tools to create reproducible workflows.
• Optimize memory use and throughput in model or systems implementations.
• Diagnose numerical and system-level failures and verify implementation quality.
• Work with coding agents as part of the expected development workflow.

The role requires substantial machine learning knowledge and technical depth in the areas described below.

• Pay: $60 to $120 per hour equivalent, paid per task that meets the project specifications.
• Schedule: Approximately 15 hours per week, with a flexible schedule.
• Location: Open to candidates in the listed countries across Africa, Asia, Europe, North America, South America, 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 field.
• Experience: Strong professional or research experience in machine learning.
• Technical skills: Practical proficiency with Python and coding agents, plus experience creating reproducible programmatic workflows and validating technical correctness.
• Relevant depth: Machine learning systems, numerical computing, performance optimization, or inference workflows.
• Helpful background: Work in an established technology company, AI laboratory, research organization, or recognized engineering environment. Exceptional open-source or academic work may also demonstrate relevant depth.
• Relevant tools may include PyTorch, JAX, NumPy/SciPy, SGLang, vLLM, llama.cpp, tokenizers, and transformers.

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 is the human work behind modern artificial intelligence. Contributors create and review code, examples, and evaluations so models and systems can learn; people with strong technical experience are needed for specialized work such as machine learning engineering and systems validation.