Senior Engineering Manager, Data Infra, Machine Learning Platform

Netflix is one of the world's leading entertainment services, with 283 million paid memberships in over 190 countries enjoying TV series, films and games across a wide variety of genres and languages. Members can play, pause and resume watching as much as they want, anytime, anywhere, and can change their plans at any time.

Machine Learning drives innovation across all product functions and decision-support needs, and building highly scalable and differentiated ML infrastructure is critical to accelerating this innovation. The Machine Learning Platform (MLP) org maximizes the business impact of all ML practices at Netflix and innovates on ML infrastructure to support key product functions like personalized recommendations, studio innovations, virtual productions, growth intelligence, and content demand modeling.

The Opportunity

We seek a seasoned engineering leader to lead the Data Infrastructure pillar within our MLP org. In this role, the successful candidate would be responsible for setting up an overall data strategy for all ML use cases at Netflix, building up roadmaps that focus on high-leverage opportunities that significantly advance the state of Netflix's ML data infra, and leading the teams in execution that generates outsized business impact.

The Data Infrastructure pillar’s charter is broad, but it mainly spans across these main areas: 

• Building scalable infrastructure for ML practitioners to acquire and load data for Netflix’s current and next-gen personalization and recommendation model training

• Developing data-related frameworks and services for training machine learning models in various content and studio use cases, including computer vision models, large language models (LLMs), and multi-modal generative models (GenAI). 

• Advancing frameworks and services for feature and label definitions, feature engineering, and data transformations that accelerate iterative model development and high-throughput large-scale model training.

This highly visible role requires building great partnerships with senior engineering and data science leaders. We are looking for a leader with experience leading successful ML infrastructure or platform teams and a strong and in-depth understanding of the experience of ML modeling teams so they can be a strong advocate for ensuring the internal customers have a world-class user experience on our ML Platform.

Expectations

• Vision: Understanding the entertainment business and how machine learning changes the business landscape will allow you to lead your team by providing inspiring context.

• Partnership & Culture: Establishing positive partnerships with both business and technical leaders across Netflix will be critical. We want you to regularly demonstrate Netflix culture values like high performance, selflessness, extraordinary candor, context over control, and curiosity and creativity in all your engagements with colleagues.

• Judgment: Netflix teams tend to be leaner than our peer companies, so you will rely on your judgment to prioritize projects and work closely with your partners and customers.

• Technical acumen: We expect Netflix leaders to be well-versed in their technical domain and use products we build so they can provide guidance for the team when necessary. Proficiency in understanding the needs of research teams and how to implement efficient ML infrastructure to meet those needs will be crucial.

• Recruiting: Your primary responsibility will be building and growing a team of outstanding engineers and managers. You will strive to make the team as excellent as possible, hiring and retaining the best and providing meaningful, timely feedback to those who need it.

Minimum Job Qualifications

• Experience leading large-scale ML platform/infrastructure teams

• 10+ years of total experience and 5+ years of management experience, with a track record of hiring and growing diverse, highly talented tenured engineers and people leaders deep into their careers to maximize their impact

• Strategic & analytical thinking skills combined with curiosity, customer empathy, and the ability to build strong relationships with cross-functional stakeholders

• Excellent at communicating context (written via memo and presentations and verbal in large meetings), giving and recei