Manage a team of engineers who are focused on:
enhancing and architecting the rollout of architecture across all new and refreshed workhorse models, solving the bottlenecks of traditional monolithic models and allowing independent, parallel policy head updates.

Drive the migration of LLM Boosters to the low-latency serving platform to dramatically reduce the time harmful ads are live (from >24 hours to ~15 minutes or real time).

Lead our agentic solutions toolkit to automate the model training lifecycle, utilizing AI agents to evaluate models and optimize prompts to completely remove human raters from the critical path.

Support the transition from complex, multi-layered FLAMeD fine-tuning to In-Context Learning (ICL) on Base Gemini models.

Scale state-of-the-art agile response platforms to onboard the next wave of high-risk policies.

Bachelor’s degree or equivalent practical experience.

8 years of experience building AI-powered products, featuring technologies such as long context windows, Retrieval Augmented Generation (RAG), or similar.

Experience building and architecting production quality Machine Learning (ML) systems.

Experience building and deploying recommendation systems models (retrieval, prediction, ranking, personalization, search quality, embedding) in production.

Experience building production quality ML systems.

2 years of experience in a people management, supervision/team leadership role.