Manager, Applied AI - Title Launch Management

Netflix; United States; Remote; USD 200,000 - 320,000; Full time

Benefits offered by this job

Health Plans

Mental Health support

401(k) Retirement Plan with employer‑m

Stock Option Program

Disability Programs

Health Savings and Flexible Spending

Family-forming benefits

Life and Serious Injury Benefits

Paid time off for full‑time employees

Flexible time off

Job summary

Netflix is seeking a senior leader to guide the Title and Launch Management (TLM) Data Science and Engineering team. You will oversee end-to-end initiatives for content launches, build robust evaluation pipelines, and implement safety guardrails to ensure fast, accurate, and scalable title launches globally.

You will mentor ML scientists and data engineers, partner across product, launch operations, and engineering, and foster a culture of ownership and continuous improvement within an inclusive

Qualifications

• 3+ years of direct management experience shipping production‑grade AI/ML software with measurable business impact.
• 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 (offline metrics, online experiments, human evaluation).
• Experience introducing automation into an established operational workflow and managing the change with teams.

Responsibilities

• 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 diversity, 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 in an agile, high-quality development culture.
• Partner with Product Management, Launch Operations, Partner Integration Managers, and multiple Engineering teams to identify opportunities, shape strategy, define roadmaps, drive execution, and deliver rollout plans.
• Cultivate durable partnerships across product, engineering, and operations; communicate complex ideas clearly to various audiences; influence priorities beyond your domain to deliver outcomes.

Skills

Management experience

Software engineering fundamentals

LLMs

RAG

Agentic architectures

Evaluation pipelines

Safety guardrails

ML evaluation methods

Automation in ops

Cross-functional collaboration

Communication

Product mindset

Tools

PyTorch

TensorFlow

Metaflow

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.

General compensation structure

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 .

Benefits

• 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
• 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.

Culture

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.

Netflix's Mission

At Netflix, we want to entertain the world. Whatever your taste, and no matter where you live, we give you access to best‑in‑class TV series, documentaries, feature films and games. Our members control what they want to watch, when they want it, in one simple subscription. We’re streaming in more than 30 languages and 190 countries, because great stories can come from anywhere and be loved everywhere. We are the world’s biggest fans of entertainment, and we’re always looking to help you find your next favorite story.