[Hiring] Engineering Manager, AI for Member Systems @Netflix

Role Description

Netflix's mission is to entertain the world by connecting members with the stories they'll love. We're hiring two engineering managers to lead the teams behind two of the most important algorithms in the recommendations space:

• Page Construction: Owns which sections appear on a member's homepage, in what order, and how the full page is composed. This team is developing a generative model that learns to build the ideal page end-to-end and is expanding into new content formats such as short-form video and games.
• Ranking: Owns the prediction of how relevant a title is to a given member in a given context. This team is driving innovation by moving the ranking stack toward an LLM-native backbone.

In this role, you will:

• Lead and grow a team of AI research scientists and AI research engineers focused on either page construction or title ranking.
• Set the technical vision and roadmap for your team, balancing investment across mature, production-grade models and newer generative approaches.
• Guide your team through the shift from traditional machine learning toward generative, LLM-based methods.
• Drive infrastructure decisions in partnership with adjacent ML and platform teams.
• Own the quality of your team's algorithms across the entire product surface.
• Partner closely with the engineering manager leading the adjacent team to ensure the two models work together as one coherent personalization experience.
• Work closely with Product Management to translate member experience goals into strategy and experimentation plans.
• Hire, develop, and retain a diverse, high-caliber team.

Qualifications

• Experience leading applied ML, ML engineering, or applied science teams on large-scale ranking, recommendation, or personalization models.
• Strong technical depth in recommender systems, ranking, or slate/page-level optimization.
• A track record guiding teams through major technical transitions.
• Strong product instincts and the ability to connect technical decisions to member experience outcomes.
• Excellent stakeholder management and communication skills.
• A track record building and leading diverse, high-performing technical teams.

Requirements

• 8+ years in applied ML/science or ML engineering, including 3+ years in a technical leadership or people management role.
• Experience with applying large language models and genAI innovations to recommendation and ranking problems.
• Experience with multi-objective optimization or slate/page-level value modeling.
• Experience managing teams operating across both mature, production-grade models and early-stage experimental work.
• Background at a consumer-scale company with AI-driven products.
• Familiarity with the full ML production lifecycle.
• Comfortable operating with a high degree of autonomy.

Benefits

• Comprehensive Health Plans.
• Mental Health support.
• 401(k) Retirement Plan with employer match.
• Stock Option Program.
• Disability Programs.
• Health Savings and Flexible Spending Accounts.
• Family-forming benefits.
• Life and Serious Injury Benefits.
• Paid leave of absence programs.
• Full-time hourly employees accrue 35 days annually for paid time off.
• Full-time salaried employees are immediately entitled to flexible time off.