Machine learning engineer in AI training

We are seeking an experienced Senior Machine Learning Engineer to contribute to AI training projects involving model development, training and inference systems, numerical computing, performance optimization, and Python engineering. This is a highly technical, coding-intensive role focused on creating, solving, reviewing, and validating challenging machine learning engineering tasks. You will build and debug implementations, develop reproducible workflows, optimize system performance, and verify results against objective correctness and performance requirements.

• Develop and validate machine learning models, training pipelines, inference systems, and supporting infrastructure.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Build reproducible workflows using Python and command-line tools.
• Debug numerical, software, and system-level failures.
• Optimize memory usage, computational throughput, and implementation performance.
• Review and validate engineering solutions against defined specifications.
• Use coding agents as part of your Python development workflow.

• Master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline.
• Strong professional or research experience in machine learning.
• Practical proficiency in Python and coding agents.
• Ability to develop, debug, and validate complex code-based solutions independently.
• Strong analytical skills and attention to technical correctness.
• Будет плюсом: Experience at an established technology company, AI laboratory, research organization, or recognized engineering environment; Exceptional academic research or open-source contributions demonstrating relevant engineering expertise; Experience with model training and inference, numerical computing, performance optimization, or reproducible machine learning workflows

• Job Type: Contract
• Work Arrangement: Fully Remote, Global
• Work Schedule: Flexible, approximately 15 hours per week
• Compensation: $57,600–$115,200 annualized equivalent ($60–$120 per hour)
• Compensation is output-based, with payment for each task that meets project specifications.
• The role is approximately 15 hours per week and pays per accepted task.