Jobs at Netflix

Supports producers and directors creating animated content through experimental GenAI production pipelines. Manages leadership calendars, creative schedules, production tracking, artist and partner communications, reviews, offsites, logistics, travel arrangements, and expenses. Acts as a bridge between creative leadership and cross-functional teams, translating creative priorities into organized production tasks while maintaining alignment with milestones and project goals.

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.

Build and evolve Netflix Account Settings and new-member onboarding experiences across frontend and backend systems. Develop TypeScript and React client experiences alongside Java-based GraphQL services, own features end to end, integrate APIs, and write maintainable, well-tested code. Collaborate with Product, Design, Data Science, and partner engineering teams to deliver experiments and reliable, high-traffic account features.

Lead a multidisciplinary data science and engineering team to build automated, production ML and agentic systems for content ingestion, launch, and distribution. Set technical vision and standards, drive cross-functional roadmaps, mentor and grow talent, and ensure measurable business impact through rigorous evaluation and execution.

Own Netflix’s regulatory Requests for Information compliance program from intake through submission. Coordinate legal, engineering, product, policy, operations, regional teams, and outside counsel; translate regulatory requirements into actionable requests; track deadlines and extensions; maintain data quality; produce leadership metrics; and improve workflows through schemas, automation, playbooks, and documentation.

Build and operate highly available, fault-tolerant distributed systems supporting Netflix’s global content creation and enterprise workflows. Responsibilities include architecting scalable infrastructure, setting technical direction, making architectural decisions, improving developer experience and observability, mentoring engineers, collaborating cross-functionally, participating in on-call rotations, and leading incident reviews. The role may involve eventing, workflow, data, messaging, and communication platforms.

Build and maintain high-scale localization platform interfaces, workflows, APIs, and services across the full stack. Develop expert React UIs with JavaScript or TypeScript, design resilient low-latency services, model data, and collaborate with design, product, and engineering teams. The role focuses on automating localization operations for internal users and external vendors, with opportunities to apply AI and LLMs to production workflows.

Build enterprise platforms and tools supporting AI-enabled animation production. Partner with senior engineers, artists, technical directors, infrastructure, and security teams to evaluate algorithms, prototype workflows, develop APIs, manage generated assets, maintain production tracking tools, monitor hardware and software usage, and standardize secure workflows across shows.

Build applications, APIs, and services supporting Netflix’s advertising media planning and full campaign lifecycle. Develop systems for campaign setup, activation, monitoring, troubleshooting, live events, performance transparency, and optimization. Collaborate with engineering, product, data science, design, and advertising stakeholders to deliver scalable ad-tech solutions. Apply knowledge of programmatic advertising, campaign workflows, audiences, creatives, measurement, forecasting, ad serving, reporting, billing, and order management.

Evolve and operate Netflix’s Studio Orchestrator platform for live-action, animation, and visual effects production. Build backend and frontend capabilities, design APIs, integrate digital content creation tools such as Nuke, Maya, and Photoshop, and connect asset management and storage systems. The role involves Python and Java development, React-based interfaces, relational databases, Kafka messaging, and scalable media workflow infrastructure supporting large-scale content production.

Build and optimize infrastructure for Netflix’s machine learning and AI systems, including distributed training, offline and post-training platforms, GPU-optimized inference, and serving. Collaborate with modeling teams on model-system codesign and solve large-scale infrastructure challenges. The internship lasts at least 12 weeks and is intended for PhD students returning to school afterward.

Conduct applied machine learning research at Netflix across areas such as recommender systems, NLP, computer vision, causal ML, agentic AI, multimodal modeling, reliable ML, and model efficiency. Develop and train models using modern frameworks and GPUs, apply distributed training and inference, build end-to-end ML pipelines, and communicate research findings. The 12-week onsite internship is based in Los Gatos, California, beginning in January 2027.

Manage Netflix’s global tax provision process, including quarterly and annual ASC 740 calculations, disclosures, cash tax and effective tax rate forecasts. Administer OneSource Tax Provision end to end, maintain documentation and audit support, analyze global tax results, and address uncertain tax positions and legislative changes. Lead process improvements, automation, and AI initiatives while collaborating with Accounting, Finance, Internal Audit, and Tax teams. Train colleagues on systems and tax accounting fundamentals.

Lead design of Netflix's ads consumer experiences, building GenAI-powered pipelines, prototyping AI-driven ad formats, ensuring privacy/regulatory compliance, collaborating with product, engineering, and data science to scale personalized advertising across surfaces.

Provide proactive administrative support to three leaders: manage complex calendars across time zones, coordinate meetings, plan offsites/events, book domestic/international travel and expenses, maintain digital organization and confidentiality, liaise with cross-functional teams, and drive process improvements to support a fast-paced ads engineering organization.

Build and operate scalable ML-powered advertising measurement platforms (Brand Lift, Incrementality, Attribution). Develop distributed data processing systems, productionize models, collaborate with data scientists, and implement backend services and data pipelines to deliver privacy-safe, scientifically rigorous ad measurement.

Design, build, and maintain end-to-end ads inventory forecasting, underwriting, and simulation systems. Work with large-scale data and distributed systems (low-latency, high-throughput), productionize ML models and optimization algorithms, collaborate with cross-functional teams, and enable forecasting and simulation use cases for Sales, Pricing, and Science stakeholders.

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.

Owns software product strategy, roadmaps, execution, and go-to-market for Netflix TV platforms and device partner technologies. The role uses qualitative insights, quantitative metrics, and field performance data to guide decisions, improve media-rendering performance, expand global feature adoption, and manage cross-functional technical delivery. Responsibilities include partner engagement, product communications, KPI reporting, risk analysis, milestone management, and scalable solutions for SmartTV and streaming-device experiences.

Owns Netflix’s title data lifecycle strategy across content formats, data models, and connected systems. The role defines title structures, entity relationships, taxonomies, operational rules, workflows, and duplicate-detection frameworks. Responsibilities include assessing upstream system impacts, partnering with product, engineering, and business teams, creating roadmaps and documentation, setting metrics, supporting automation, and influencing stakeholders without direct authority. The position requires strong data governance, analytical, communication, project management, and cross-functional collaboration skills.