Jobs at Netflix

Lead cross-Finance programs from ideation to implementation, define scope and success metrics, develop project charters and work plans, manage risks and dependencies, align stakeholders and engineering/product teams, produce executive communications, and drive change management for Finance processes (Order to Cash, Procure to Pay, Record to Report, Forecast to Delivery).

Support and maintain high-availability Netflix apps and device firmware across multiple TV platforms. Manage app store updates, investigate monitoring alerts and JS component canaries, execute configuration and CI updates, develop playbooks, and drive automation and tooling improvements to reduce operational drag.

Manage global treasury operations including cash forecasting, liquidity, FX settlements, bank account management, and intercompany analysis. Liaise with banking partners, support automation and system implementations, validate/reconcile data for Treasury reporting, train business partners on online banking, and lead ad-hoc treasury projects to improve processes and controls.

Partner with Product, AP, Accounting, FP&A and IT to manage source-to-pay operations: vendor management, PO setup, invoice processing, accruals/month-end close, reporting, and workflow automation.

Lead design and implementation of Metaflow to build, manage, and scale ML applications. Partner with ML researchers, OSS community, and cross-functional teams to improve ML platform reliability, CI/CD, observability, and developer velocity.

Design and implement efficiency improvements for large-scale deep neural networks and LLM training/serving. Develop optimizations (quantization, pruning, distillation, efficient fine-tuning), work on ML hardware/software accelerator integration, and build scalable training and serving infrastructure in collaboration with scientists and cross-functional teams.

Design and implement high-quality iOS features and core infrastructure using Swift and advanced UIKit/Core Animation APIs. Architect maintainable client code, write automated tests (XCTest, XCUITest), run A/B experiments, and collaborate with product, design, and partner engineering teams to deliver performant, accessible user experiences.

Design, implement, and evaluate alignment and quality metrics for member-facing LLM and recommendation systems. Build tools and pipelines for RLHF, reward modeling, fine-tuning, and human-in-the-loop evaluation. Collaborate cross-functionally, write production-quality code, and improve model robustness and metrics using member feedback and large-scale distributed systems.

Design, develop, deploy, and operate high-impact ML models for Payments and Growth. Partner with business stakeholders to identify opportunities, run offline experiments and online A/B tests, and collaborate with ML platform and engineering teams to productionize scalable end-to-end solutions and improve ML infrastructure.

Build and operate resilient, high-scale, low-latency microservices and APIs (gRPC/GraphQL/REST) using OO languages (Java/C#). Design data models, optimize concurrency and performance, ensure observability, and collaborate with cross-functional teams to support content promotion, localization, and distribution workflows at Netflix.

Build and operate full-stack observability features that combine logs, metrics, and traces into actionable insights. Design, develop, test, deploy, and support backend APIs (GraphQL/Node.js) and frontend experiences (React/TypeScript) while collaborating with Telemetry and Monitoring teams at Netflix scale.

Lead development and enforcement of advertising policies for Netflix's ad-supported tier. Serve as functional expert across verticals, manage complex global policy projects, align cross-functional stakeholders, and balance scalability with regional sensitivities to protect member experience and advertiser outcomes.

Design, implement, and deploy large-scale machine learning and optimization algorithms for ad ranking. Build and evaluate models, create online/offline evaluation frameworks, partner with product to define objectives and constraints, and communicate results to stakeholders to drive ad quality and performance.

Lead design, implementation, and operation of high-impact ML models for Growth & Commerce. Build end-to-end production ML systems, run offline experiments and online A/B tests, partner with scientists, engineers and product teams, and improve ML infrastructure for availability, scalability, and cost efficiency.

Lead a team of senior data scientists in analytics, experimentation, and machine learning to partner with engineering teams, scale analytics, innovate methodologies, and drive high-impact insights to optimize Netflix streaming products.

Lead and scale product operations for Netflix Ads Platform by building operational frameworks, release management, OKR tracking, support triage, product ideation, reporting, and stakeholder evangelism. Partner with Product, TPM, Engineering, Data, and cross-functional teams to operationalize processes, drive improvements, and enable efficient product lifecycle management.

Design and implement ML and CGI tools that integrate generative AI to support visual effects artists. Collaborate with researchers, engineers, product and creative stakeholders, develop scalable algorithms, build development infrastructure, and promote software engineering best practices.

Partner with Studio & Creative Production to define analytical problems, build metrics, prototypes, dashboards, and analyses. Source and model data with Data Engineers and Data Scientists, apply ETL and data‑warehousing best practices, and influence strategic decisions using SQL/Python/R/Scala and visualization tools like Tableau.

Lead and mentor a mobile engineering team to define and execute client/UI roadmaps for Android and iOS, drive technical and product decisions, collaborate on architecture with cloud and device experts, and improve developer experience and performance to enable rich, high-performance streaming experiences.

Partner with content verticals to define analytics strategy, design scalable metrics and dashboards, lead data architecture for new initiatives, mentor engineers, and translate data science outputs into actionable insights to drive content decisions.