- Develop and validate machine-learning models and training pipelines
- Implement model components, data pipelines, and evaluation systems
- Build reproducible programmatic workflows using Python and command-line tools
- Create and solve challenging machine-learning engineering tasks
- Optimize memory and throughput for existing machine learning systems
- Debug numerical or system-level failures in implemented models
- Verify that implementations meet correctness and performance specifications
Requirements
- Master's degree or PhD in a related quantitative discipline
- Strong skilled or research experience in machine learning
- Practical proficiency with Python and coding agents
- Experience at a recognized technology company or research organization
- Ability to demonstrate depth with equivalent tools if necessary
- Exceptional open-source or academic experience is a plus
- Willingness to start tasks within 24 48 hours after onboarding