Senior Engineering Manager - Model Inference & Serving, AI Platform

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right title for them through personalization, to enhancing our understanding of our audience and content slate, to optimizing our payment processing and other revenue-focused initiatives. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation. More recently, rapid innovation in large language models (LLMs) has significantly advanced state-of-the-art technology in various areas of personalization, including search and recommendation experiences. ### The Opportunity We are seeking a Senior Engineering Manager to lead the Model Inference & Serving pillar within the ML Platform organization. This is a pivotal, high-impact "leader of leaders" role, responsible for setting the strategic vision and execution across multiple teams that deliver the core model serving infrastructure for all of Netflix. Your leadership will shape the future of ML model delivery, experimentation, and operational excellence at a global scale.

You will:

• Set the vision and strategy for all aspects of model inference and serving at Netflix, ensuring our platform supports the next generation of ML innovation, including LLMs, GenAI, and real-time personalization.
• Lead and develop a cohort of engineering managers and technical leads responsible for core functions, including model routing, inference systems, experimentation, serving frameworks, and the performance and scalability of model serving at Netflix.
• Drive cross-team and cross-functional alignment, collaborating with ML researchers, product engineering, infrastructure, and platform partners to maximize business and member impact.
• Champion operational excellence and continuous improvement, ensuring reliability, scalability, and cost-effectiveness across all model serving systems. ### ### Key Responsibilities Vision & Strategy
• Define and communicate the pillar's multi-year vision, technical strategy, and roadmap.
• Anticipate future platform and business needs, especially as ML architectures and use cases evolve.
• Drive the transition from legacy, domain-based serving to a unified, modular, and domain-agnostic serving platform. Leadership & People Development
• Manage and mentor engineering managers and technical leads; build a strong leadership bench.
• Foster a culture of high performance, candor, innovation, and inclusion, aligned with Netflix's values.
• Attract, hire, and retain outstanding talent across the pillar. Technical Direction & Operational Excellence
• Set and uphold technical standards for reliability, scalability, and performance across all teams.
• Oversee development of foundational serving infrastructure: real-time/batch inference, frameworks, experimentation, control plane, and tooling.
• Ensure robust support for diverse model types (deep learning, LLMs, bandits, etc.), hardware targets (CPU/GPU), and SLAs.
• Own operational health and reliability at scale, including observability, SLOs, and incident response. Cross-Functional & Stakeholder Engagement
• Build and maintain strong partnerships with ML practitioners, product engineering, infrastructure, and platform teams.
• Represent the Model Serving pillar to Netflix senior leadership, clearly communicating the vision, progress, and priorities.
• Influence and drive alignment on platform direction, investment, and priorities. ### ### What You Need to Succeed
• Proven success managing multiple managers in high-scale ML infrastructure/platform environments.
• 10+ years of technical experience, with 5+ years in engineering management roles.
• Deep expertise in ML model serving, distributed systems, and high-scale production environments.
• Strategic thinking with a track record of delivering complex, cross-team initiatives.
• Excellent communication and stakeholder management skills.
• Experience driving organizational change and leading through ambiguity.
• Experience with modern ML frameworks (e.g., PyTorch, TensorFlow), inference engines (e.g., Triton, vLLM), and experimentation platforms is a strong plus.
• MS/PhD in Computer Science, Engineering, or related field, or equivalent experience preferred.

### Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $676,000.00 - $1,195,000.00. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here. Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.