Senior Engineering Manager, YouTube, Recommendations ML
About The Position
The Senior Engineering Manager will lead a small team developing large machine learning models for YouTube recommender systems. The role calls for expertise in machine learning and continued development and innovation in ranking, retrieval, and large language models. Work may include building models, analyzing user data to identify gaps and opportunities, and evaluating model architectures at the intersection of model, hardware, and infrastructure co-design to improve performance and efficiency. The workstream may focus on Large Recommender Models, using Semantic IDs and Gemini-based LLM models for especially difficult recommendation use cases. The manager will align research directions with cross-YouTube and cross-product-area partners. The position also involves providing technical leadership across teams and locations, managing project goals and contributing to product strategy, and overseeing large-scale project deployments across multiple international sites.
Requirements
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- 8 years of experience designing and building large-scale machine learning models.
- 8 years of experience building, testing, maintaining, and launching software products that require running and analyzing experiments and working with user data.
- 5 years of experience in people management, supervision, or team leadership.
- Experience creating and aligning cross-organizational technical roadmaps across multiple software engineering, research, product management, and data science teams.
- Experience conducting research or applied research on recommender systems models or related areas such as ranking, retrieval, or user-related areas.
Nice To Haves
- Master's degree or PhD in Computer Science or a related technical field.
- Experience guiding research programs in relevant areas for small teams.
- Experience with hardware ML model and framework co-design.
- Experience optimizing compute or hardware capacity.
- Publications in recommender systems, LLMs, or large-model performance and efficiency.
Responsibilities
- Set and communicate team priorities that support broader organizational goals, and align strategy, processes, and decision-making across teams.
- Set expectations for individuals based on their level and role and organizational goals; meet regularly with them to discuss performance and development and provide feedback and coaching.
- Develop and evolve the long-term technical goals and roadmap within and beyond the scope of the teams, anticipating future requirements and infrastructure needs.
- Oversee systems designs across the broader area and review product or system development code to solve ambiguous problems.
- Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of advanced recommendation systems.
- Align research directions with cross-YouTube and cross-product-area partners.
Benefits
- Equity
- Benefits
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What This Job Offers
Job Type
Full-time
Career Level
Senior
