Job description

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. What you will do • 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. What we are looking for • 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) and integrating them into continuous improvement processes. • Experience introducing automation into an established operational workflow earning operator trust, designing the human-in-the-loop handoff, and managing the change with the teams whose work is being automated. • Cultivate open communication, empowering team members to give feedback and recognize achievements and growth areas. • Strong product mindset; can translate high-level goals into clear team priorities and plans. • Skilled at prioritizing and aligning team efforts with business objectives, able to adjust direction based on impact and new information. • Effective collaborator who builds productive cross‑functional partnerships with product and engineering. • Uses data, feedback, and small experiments to reduce ambiguity and make sound decisions. • Communicates clearly with their team, stakeholders, and global partners. Nice to have • Experience in the media technology domain (e.g. content processing, digital asset workflows, creative tools) • Technical proficiency with hands-on experience across the AI/ML lifecycle—ranging from traditional frameworks and MLOps platforms (e.g., PyTorch, TensorFlow, Metaflow) to modern LLM orchestration, agentic frameworks (e.g., LangGraph, DSPy, Agent SDK), and vector databases. 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 $436,000.00 - $710,000.00. 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.

Requirements

Must-haves

Oversee a diverse portfolio of end-to-end initiatives that advance Netflix’s title launch strategy and support our rapidly growing content slate.
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.
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.
What we are looking for
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) and integrating them into continuous improvement processes.
Experience introducing automation into an established operational workflow earning operator trust, designing the human-in-the-loop handoff, and managing the change with the teams whose work is being automated.
Cultivate open communication, empowering team members to give feedback and recognize achievements and growth areas.
Strong product mindset; can translate high-level goals into clear team priorities and plans.
Skilled at prioritizing and aligning team efforts with business objectives, able to adjust direction based on impact and new information.
Effective collaborator who builds productive cross‑functional partnerships with product and engineering.
Uses data, feedback, and small experiments to reduce ambiguity and make sound decisions.
Communicates clearly with their team, stakeholders, and global partners.

Nice-to-haves

Experience in the media technology domain (e.g. content processing, digital asset workflows, creative tools)
Netflix is a unique culture and environment. Learn more here .

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimachine learningagilemlllm

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

401(K)

Paid Time Off