Jobs at Netflix

Own the strategy, roadmap, and lifecycle of Netflix Ads’ identity and audience onboarding platform. Lead development of identity graphs, APIs, advertiser integrations, partner ingestion, and identifier storage. Collaborate with engineering, science, design, sales, marketing, legal, and policy teams to launch scalable advertiser-facing products. Drive identity governance, privacy-forward data management, stakeholder alignment, and adoption across the advertising ecosystem.

Own the strategy, roadmap, and end-to-end delivery of Netflix’s CTV advertising billing and financial workflow products. Responsibilities include reconciliation, invoicing, revenue recognition support, dispute handling, AI-assisted automation, requirements definition, metrics, documentation, and cross-functional collaboration with Engineering, Finance, Sales, Ad Operations, and Design.

Own product vision and AI strategy for internal catalog management and content-understanding tools. Lead roadmap, incubate ML/LLM capabilities, collaborate with researchers and engineers, translate AI advances into scalable internal products, and measure impact through hypothesis-driven evaluation.

Build and scale Netflix Ads sales products, including advertiser data strategy, governance, go-to-market architecture, sales workflow automation, AI-powered agentic experiences, revenue reporting, and forecasting. Partner with sales, engineering, design, ad operations, marketing, strategy, policy, and legal teams to improve sales productivity and advertiser outcomes.

Own ads experimentation and incrementality measurement products for advertisers, agencies, and measurement partners. Partner with engineering, UX, data science, sales, legal, and other teams to define strategy, prioritize the roadmap, launch products, and drive adoption. Apply causal inference and experimentation methodologies, including A/B testing, conversion lift, brand lift, multi-armed bandits, search lift, and geo lift, while supporting Netflix’s advertising measurement ecosystem.

Design, build, and operate scalable, low-latency backend services for ad decisioning, targeting, pacing, and policy enforcement. Own APIs, data models, observability, capacity planning, incident response, and ensure platform reliability at massive scale while maintaining ad-tech domain expertise.

Design and build high-volume, low-latency Conversion APIs to ingest consented advertiser events (server-to-server, pixel, batch). Implement streaming architectures (Kafka/Flink), deduplicate and enrich identity/attribution data, enable measurement, optimization, retargeting and reporting while ensuring privacy, compliance, and cross-functional collaboration.

Design and build large-scale ad tech systems across inventory, serving, measurement, forecasting, identity, and campaign management. Drive architecture, set technical direction, collaborate with ad operations and cross-functional partners, and deliver high-performance, privacy-safe cloud services and data pipelines for Netflix Ads.

Design, build, and operate low-latency, high-QPS ML model serving and feature systems for real-time ad decisioning. Scale inference, ensure online/offline feature consistency, productionize ranking and scoring models, implement monitoring and simulation infrastructure, and partner with Data Science to validate and rollout models safely.

Build and operate large-scale Ads Identity Graph and Identity Resolution systems (deterministic and probabilistic) in batch and near-real-time. Integrate identifier collection flows, DSPs, programmatic platforms, and data clean rooms while enforcing privacy, consent, and data governance. Handle extremely large datasets with big-data tools like Spark and design high-throughput, low-latency distributed systems. Collaborate cross-functionally on ad-targeting, measurement, and privacy-preserving solutions.

Lead design and execution of Netflix's advertising design system and core capabilities. Partner with central design system teams, research and define ads-related features (access, notifications, support), craft design briefs, and collaborate with engineers, product, data, and writers to build extensible React components and scalable workflows for global ad and live-streaming experiences.

Lead product development for Live event ad-serving infrastructure, handling unpredictable traffic, yield optimization across direct and programmatic demand, and cross-functional launches. Define metrics, iterate features, and partner with engineering, sales, ad ops, data science, and external partners to enable seamless Live ad delivery and drive advertiser outcomes.

Lead personalization product strategy and execution, partnering with ML scientists, engineers, designers, and research to improve recommendations. Define roadmap, prioritize experiments and evals, deliver consumer-facing ML products, and drive business impact across cross-functional teams.

Lead design and delivery of Ads Policy infrastructure: define architecture, governance, evaluation, and integrations for ad policy enforcement across campaign setup, creative review, serving, and reporting. Drive cross-team technical strategy, build scalable distributed systems, mentor engineers, and ensure operational excellence for production-critical ad systems.

Lead Pre-Sales and Revenue Management product strategy for Netflix Ads. Partner with sales, engineering, design, data science, and cross-functional teams to prioritize roadmap, launch revenue planning and inventory management products, leverage analytics to identify revenue opportunities, and drive adoption to maximize ad yield and monetization.

Build and own UI features for Netflix’s TV application across streaming sticks, smart TVs, and cable boxes. Collaborate with product, design, algorithm, and engineering teams to create and refine consumer experiences. Develop TypeScript and JavaScript features using React and Redux, optimize for performance- and memory-constrained devices, conduct A/B testing, and write automated tests using Jest-based frameworks.

Owns product operations for the Content Experience Innovation team, including operating rhythms, OKRs, QBRs, portfolio visibility, roadmaps, tooling, workflows, and leadership communications. Leads cross-functional innovation programs across Product, Engineering, Design, Content, and other teams, improving efficiency through scalable processes, AI, and automation. Partners with senior leadership to shape transformation initiatives and align product development with broader business goals.

Owns end-to-end human evaluation programs for Netflix recommendation quality. Partners with product, ML, data science, UX, engineering, and vendors to design evaluation frameworks, rubrics, metrics, and workflows. Manages annotation capacity, SLAs, costs, rater onboarding, calibration, quality assurance, and delivery timelines. The role also improves operational efficiency, resolves blockers, and translates recommendation strategy into scalable evaluation programs.

Build and maintain data models, pipelines, metrics, dashboards, and analytics supporting Netflix’s advertising identity graph, entity matching, and identity resolution systems. Evaluate match quality, coverage, graph stability, and data drift; collaborate with engineering, data science, product, and identity providers; and communicate technical insights and trade-offs to technical and non-technical stakeholders.

Lead ML initiatives to improve Sales productivity and automation: define roadmap, design and deploy production ML models and AI agents, build measurement pipelines with analytics engineers, iterate from performance and seller feedback, and act as senior technical partner across product, engineering, and Sales to drive measurable revenue impact.