Responsibilities
- Lead the complete machine learning lifecycle, from concept and research through design, deployment, monitoring, and ongoing model retraining.
- Develop and apply comprehensive frameworks for training, evaluating, stress-testing, and observing ML/AI systems to ensure sustained performance and prevent degradation over time.
- Solve large-scale, real-world performance and efficiency challenges, ensuring models meet quality and latency requirements under production demands.
- Guide technical strategy as a senior individual contributor and provide mentorship to less experienced engineers.
- Support the enhancement of automated testing across unit, integration, and functional levels.
- Take full ownership of services and components, including active participation in on-call rotations.
