Machine Learning Task Engineer
Job Description
Develop coding-intensive machine-learning tasks and objective checks for model correctness and performance.
What you will do
• Implement or modify models, training pipelines, inference systems and numerical components.
• Create reproducible Python and command-line workflows, including data processing and evaluation.
• Investigate numerical or system failures and improve memory use or throughput.
• Validate that implementations meet stated accuracy, correctness and performance requirements.
Required background
• A master’s or doctorate in CS, ML, AI, applied mathematics, statistics, engineering or a closely related quantitative discipline.
• Substantial professional or research ML experience.
• Practical Python ability and experience using coding agents in the workflow.
Preferred background
• Depth in relevant tools such as PyTorch, JAX, NumPy, SciPy, SGLang, vLLM, llama.cpp or Hugging Face Transformers/Tokenizers; equivalent tools are acceptable.
• Experience at a recognized technology, AI or research organization is strongly preferred, while exceptional academic or open-source experience may also qualify.
Location and eligibility
• Fully remote; global participation is explicitly supported.
Availability
• Approximately 15 hours per week, with flexible days. Accepted-task specifications, submission requirements and start timing are agreed before work.
Pay and engagement
Per accepted task; fee agreed before work
Payment is for a task meeting the agreed acceptance criteria. The fee and acceptance requirements are confirmed before you begin.
Amounts are in USD. The applicable rate or fee and work requirements are agreed before you begin.