Circuit

Full-stack Engineer

• Own the engineering work that moves ML capabilities from research into production. You write the code, you ship the feature, you are accountable for it working.
• Work across the AI/ML team to understand their work and make sound engineering judgments about what is ready to ship and how to get it there.
• Build and maintain model serving and evaluation infrastructure. You understand the stack deeply, including how inference works, why serving choices matter, and what the tradeoffs are.
• Lead implementation of ML-driven features, coordinating with the research team and the rest of engineering to get things shipped.
• Debug production systems including edge cases and failure modes in ML pipelines and retrieval systems.
• Establish and improve observability, debugging, and testing practices for ML systems.
• Build and maintain evaluation systems, including datasets, scoring approaches, and repeatable testing to detect regressions.
• Improve the reliability, testability, and maintainability of the ML codebase without slowing down iteration.
• Use AI coding tools fluently as a core part of your daily workflow, with the judgment to evaluate what they produce and catch errors before they ship.

Principal Engineer, ML Systems