Overview
Engineering Manager - Model Development, Machine Learning Platform at Netflix. The Model Development & Management (MDM) team builds and evolves the unified developer experience—SDKs, frameworks, and libraries—that powers end-to-end model creation at Netflix. We focus on maximizing practitioner velocity while making infrastructure complexity invisible, integrating tightly with data/feature, training, serving, and evaluation pillars.
Machine Learning Platform (MLP) drives innovation across product functions and decision-support needs, and building highly scalable and differentiated ML infrastructure is critical to accelerating this innovation. 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.
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, high‑ownership culture.
To Succeed In This Role, You Will Need
- 10+ years of software engineering experience and 3+ years building and leading engineering teams.
- Experience leading teams responsible for building state‑of‑the‑art ML model development platforms that cover the full model development lifecycle.
- A track record working on distributed ML infrastructure that spans laptop‑to‑cluster execution, supports multi‑node GPU training, and serves large‑scale models (recommenders, computer vision, LLMs, multimodal GenAI).
- Deep familiarity with containerization/orchestration, dependency and environment management (e.g., pinned specs, environment locks), and secure packaging practices for reliable, repeatable runs.
- Proficiency with ML frameworks and commercial ML/AI infrastructure, such as PyTorch, SageMaker, Ray, and Hugging Face, etc.
- Strong technical acumen: act as a credible technical advisor to the team, set and enforce a high‑quality bar for code and system design, and mentor engineers across levels.
- A passion for translating the needs of ML practitioners into platform offerings with an emphasis on automation and self‑service capabilities.
- Strong communication and collaboration skills, with the ability to build durable relationships with internal customers and external partners.
- Demonstrated ability to develop, drive, and execute a technical vision and roadmap.
- A track record of attracting top talent and growing a high‑performing, diverse team of tenured engineers to deliver results in a fast‑paced environment.
- Experience managing a hybrid team with partners and team members distributed across U.S. geographies and time zones.
Additional Notes
In this role, you will work with diverse teams across Netflix platforms and contribute to an environment that values inclusion and innovation. Netflix is an equal‑opportunity employer and offers accommodations for disabilities during the hiring process.
EEO and Employment Facts
We are an equal‑opportunity employer and celebrate diversity. 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.
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