Engineering Manager Model Development Machine Learning Platform

Netflix is one of the world's leading entertainment services, with over 300 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. Our Machine Learning Platform (MLP) maximizes the impact of ML by building differentiated, scalable infrastructure that accelerates research and product iteration across recommendations, growth, studio, content understanding, and emerging generative AI use cases.

The Opportunity:

The Model Development & Management (MDM) team builds and evolves the unified developer experience-SDKs, frameworks, and libraries-that powers end-to-end model creation  focus on maximizing practitioner velocity while making infrastructure complexity invisible, integrating tightly with data/feature, training, serving, and evaluation pillars. Our portfolio-with-paved-paths strategy (Metaflow and other libraries exposed through one opinionated SDK) supports teams from a single data scientist to 100+ MLEs and model scales from ~10M to 100B+ parameters-spanning classic personalization, content understanding, and multimodal GenAI.

We are looking for an experienced ML/AI infrastructure engineering leader to manage MDM and drive the next generation of Netflix's model development platform! You will lead the team to architect, build, test, and launch a cohesive SDK and set of opinionated templates that let practitioners scaffold projects, configure and execute runs (from laptop to tightly coupled multi-node GPU training), track experiments and lineage, package models with evaluation hooks, and promote them confidently.

Your work will enable partners across content, studio, consumer, ads, and games to develop and iterate on large-scale models-including LLMs, recommenders, computer vision, and foundation models-throughout the full lifecycle from early research and experimentation to productization and ongoing optimization. Success will be measured by concrete developer-experience KPIs such as time-to-first successful remote run, run success rate (ex-user code), mean time to actionable diagnosis, adoption of paved paths, and template reuse.

We are a highly collaborative team. You will operate cross-functionally with Training Platform and Offline Inference, Serving Systems, Feature/Data Infrastructure, and MLP Tooling to deliver a seamless, consistent experience end-to-end. To thrive here, you bring a strong ML infrastructure background (SDK/CLI design, packaging and environments, experiment tracking/lineage, observability), excellent product taste for developer experience, and the judgment to balance paved-path simplicity with power-user control.

You'll design for extensibility as the space evolves, keep interfaces stable with clear deprecation policies, and prioritize measurable outcomes that lift practitioner velocity across Netflix.

In this role, you will:

• Partner with ML practitioners and adjacent pillars (Feature/Data, Training, Serving, Evaluation) to translate needs into a unified developer experience that hides infrastructure complexity while preserving expert control.
• Drive the strategy and vision of the Model Development SDK-owning the portfolio of existing and new products, making build‑vs‑buy choices, and integrating libraries/frameworks into the unified platform.
• Build and execute a metrics‑led roadmap: define Developer Experience (DX) KPIs, plan incremental delivery and migrations, and demonstrate impact through adoption and reuse.
• Maintain and evolve current product offerings that are widely adopted both in OSS and internally (e.g., Metaflow).
• Communicate progress, milestones, and risks to stakeholders, customers, and senior leadership.
• Hire, grow, and coach a diverse team across Core Frameworks and User Experience pods (and incubate Exploratory Infra as needs emerge), fostering an inclusive,…