Jobs at Netflix

Design and architect AI-native, agentic platform systems for the Netflix Ads Suite. Define scalable UI patterns, schemas, and machine-consumable documentation; build AI-assisted prototypes and operationalize agentic workflows with engineering. Steward AI-generated outputs, mentor designers on AI fluency, and bridge Product Design with ML Engineering to ensure ethical, scalable, and performant platform infrastructure.

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.

Lead development and operationalization of an enterprise crisis management and resilience program: design frameworks, playbooks, governance, exercises, and training; coordinate cross-functional crisis response and executive communications; run crisis activations as needed; integrate business continuity and risk into preparedness and recovery planning.

Lead Netflix's global Physical Identity and Access Management program: design and operate PIAM systems, set policies, manage access credentials, integrate AI/biometrics, audit compliance, centralize access logs, collaborate with HR/IT/IAM partners, shape technology roadmap, track PIAM metrics, and produce documentation and training. Requires global stakeholder engagement and ~25% travel.

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.

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.

Develop, optimize, and deploy scalable predictive ML models to inform content strategy, valuation, scheduling, and performance. Own end-to-end model lifecycle (feature engineering, training, evaluation, deployment, monitoring) and partner with analytics, data engineering, MLOps, and content teams to scale production solutions and influence ML infrastructure.

Lead product strategy and roadmap to expand Netflix ad supply and monetize content. Manage ad-tech product lifecycle, design integrations with ad servers/SSPs/DSPs, enable audience targeting and onboarding, define success metrics, and collaborate with cross-functional product, engineering, and business teams to launch and iterate features.

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 vision, strategy, and execution for the Ads Targeting Platform, architecting audience and contextual signal ingestion, taxonomy, normalization, and storage. Partner with engineering, data science, sales, and GTM to enable forecasting, media planning, and campaign activation. Prioritize roadmap, govern signal quality and compliance, shape GTM packaging, and align stakeholders to drive advertiser outcomes and scale.

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.

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.

Lead product vision and roadmap for Netflix Ads Laboratory Infrastructure to enable experimentation across supply and demand. Partner with engineering, data science, design, sales, ad ops, and legal to build scalable experiment lifecycle tooling, ensure high availability, self-monitoring, and data governance, and drive adoption while addressing privacy and regulatory requirements.

Lead technical direction and implementation for real-time ad decisioning and optimization: architect low-latency ML model serving, build pacing and budget-delivery systems, scale ad-serving infrastructure, enable simulation and testing frameworks, drive platform modularization, and own reliability, observability, and incident response across the ads optimization stack.

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.

Develop long-range capacity forecasts and translate demand signals (bandwidth, storage, network) into actionable capacity plans. Run scenario and what-if analyses, monitor infrastructure performance, coordinate deployments, build modeling and automation tools, manage capacity risks, and collaborate cross-functionally to inform investment and scaling decisions for Open Connect Studio Infrastructure.

Build and maintain low-latency, highly available distributed data systems and services to deliver high-quality data for product, analytics, and ML. Partner with data scientists and product teams to design scalable, observable, multi-tenant data products using batch and real-time processing frameworks. Ensure 24x7 reliability, monitoring, and operational excellence while owning end-to-end delivery.

Build and own internal data visualization web applications for content reporting. Partner with product, data scientists, and R&D to integrate multiple data sources, design intuitive charts, iterate on UX based on feedback, and surface metrics and predictive analytics for business stakeholders.

Design, productionize, and deploy machine learning forecasting models for ad inventory and campaign performance in low-latency, real-time advertising environments. Build scalable simulation, budgeting, and pacing systems; collaborate with cross-functional teams to deploy models at scale and optimize ad monetization.

Lead research and experimentation to measure ad campaign performance and effectiveness. Design evaluation frameworks, build measurement solutions, develop models for lift, conversion, and attribution, run experiments and analyses, partner with product/engineering/design/sales, present insights, mentor teammates, and foster technical community and culture.