Manager, Applied AI - Title & Launch Management

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.

The Title and Launch Management (TLM) team is responsible for building and innovating the technology foundations that enable the ingest, setup, launch, and global distribution of all types of entertainment on Netflix—including series, movies, games, ads, live events, trailers, and more. TLM acts as the bridge between the title creation lifecycle and the consumer experience, ensuring that launching titles on Netflix is efficient, flexible, accurate, and scalable. Our team’s goal is to make launching titles as seamless as possible, supporting both operational and creative needs across the company.

The TLM Data Science and Engineering team drives automation and operational excellence in how we launch content. The team owns the data foundations, measurement workflows, reporting, and observability tooling, as well as AI/agentic solutions that make title launches faster, more automated, and less error‑prone from ingest through to being live and healthy on service. We develop systems that identify and classify issues, automate resolution across a broad set of teams and systems, apply reasoning to identify risk, and increasingly, automate launch decisions.

* Oversee a diverse portfolio of end-to-end initiatives that advance Netflix’s title launch strategy and support our rapidly growing content slate.

* Lead the team in developing rigorous, scalable evaluation pipelines and safety guardrails to monitor launch speed, content and format diversity, technical spec compliance, and risk across our global catalog; analyze production failures and drive systematic improvements to model and workflow reliability.

* Guide the team in designing feedback loops and data infrastructure that continuously bring high-quality real-user data into evaluation and training pipelines to improve performance over time.

* Coach, hire and develop a team of machine learning scientists, analytics engineers, and data engineers, fostering an agile, high-quality development culture grounded in robust software engineering practices.

* Partner closely with Product Management, Launch Operations, Partner Integration Managers, and multiple Engineering teams to identify opportunities, shape strategy, define roadmaps, drive execution, and deliver well-structured rollout plans.

* Cultivate durable partnerships across product, engineering, and operations; communicate complex ideas clearly to various audiences; connect the dots across teams; and influence priorities beyond your immediate domain to jointly deliver outcomes.

* Foster a culture of ownership and timely, reliable delivery against the roadmap while acting as a trusted technical advisor who balances business goals with strong engineering practices and continuous improvement.

* Create an environment where everyone feels empowered, accepted, and respected, and where diverse perspectives are actively encouraged and valued.

* 3+ years of direct management experience shipping production-grade AI/ML software with measurable business impact, building and managing high-performing, inclusive teams, attracting top talent, fostering accountability, and ensuring all voices inform decisions.

* Proficiency in software engineering fundamentals and LLMs, RAG, and agentic architectures

* Strong track record of designing and implementing evaluation pipelines for AI/ML products. Experience building safety guardrails to manage business risk and feedback loops for continuous improvement of models

* Familiarity with ML evaluation methodologies (e.g., offline metrics, online experiments, human evaluation)