Junior Machine Learning Engineer

What You'll Do8

• Build and validate machine learning models, training pipelines, and inference systems.
• Implement model components, data pipelines, evaluation systems, and numerical methods.
• Create reproducible programmatic workflows using Python and command-line tools.
• Solve challenging machine learning engineering tasks that involve model modification or implementation.
• Construct training or inference workflows that can be reproduced and verified.
• Optimize memory usage or throughput for model runs.
• Debug numerical or system-level failures and confirm the implementation meets correctness and performance requirements.
• Review and validate machine learning tasks submitted by others.

Requirements6

• BS in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative field.
• Strong professional or research experience in machine learning.
• Practical proficiency with Python and coding agents.
• Experience using coding agents with Python in your workflow.
• Ability to work with command-line tools and build reproducible workflows.
• Comfort with a coding-heavy role focused on model development and performance.

Preferred Qualifications2

• Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment.
• Exceptional open-source or academic experience may also qualify.

Who Should Apply

This role suits a junior machine learning engineer with a quantitative degree and solid Python skills, including hands-on use of coding agents. You should be comfortable debugging numerical issues and building reproducible training or inference pipelines. If you have research or open-source experience that shows depth, that counts too.

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