Top Tech Jobs & Startup Jobs

Leads Netflix’s U.S. federal policy advocacy, including developing strategies, analyzing legislation, monitoring congressional activity, building policymaker relationships, preparing advocacy materials, advising internal stakeholders, and collaborating with consultants, trade associations, and civil society partners on technology, media, and telecommunications policy.

Manage the Applied AI team supporting Netflix title launches. Lead AI/ML evaluation pipelines, safety guardrails, feedback loops, data infrastructure, automation, and reliability improvements. Hire, coach, and develop machine learning scientists, analytics engineers, and data engineers. Partner with product, operations, and engineering teams to define strategy, roadmaps, and rollouts while ensuring responsible, scalable delivery.

Leads operational planning and execution for Netflix content and business product domains. Responsibilities include supporting annual and quarterly planning, tracking OKRs and initiatives, maintaining documentation and visibility systems, coordinating events, producing leadership reporting, improving operating models, and driving adoption of AI-enabled workflows. The role partners with Product, Design, Engineering, Data Science, and administrative teams and may manage high-priority cross-functional programs end to end.

Administer and optimize Netflix’s global Workforce Management platform and integrations. Responsibilities include data validation, system configuration, user provisioning, licensing, Tier 1 troubleshooting, third-party tool integration, documentation, and process improvement. The role partners with Operations, Engineering, Data Science, Product & Technology, vendors, and other IT teams to maintain platform reliability, data integrity, security, and scalable workforce management solutions.

Build and operate Netflix Cloud developer platforms, infrastructure-as-code systems, Tier-0 control planes, and AI-agent sandboxing primitives. Own the developer experience across the software delivery lifecycle, make product and platform design decisions, and ensure reliability, scalability, security, and cost efficiency. The role requires production ownership of developer platforms, strong distributed-systems expertise, comfort with ambiguity, and proficiency across multi-language, multi-service codebases.

Lead research and development of generative AI and recommendation solutions for Netflix promotional assets and content discovery. Responsibilities include tracking LLM research, developing summarization and LLM-as-judge systems, training and evaluating models, optimizing generated content for audience impact, partnering with engineering teams, defining ML roadmaps, and communicating technical strategies to stakeholders.

Partners with product, business, content operations, and data teams to define measurement frameworks, analyze media production workflows, build prototypes and dashboards, strengthen data models, and provide data-driven insights for strategic decisions. The role focuses on measuring GenAI-enabled production improvements, operational efficiency, creative flexibility, and innovation impact while influencing stakeholders and leadership.

Develop foundational image and video generation models for Netflix’s creative technology ecosystem. Responsibilities include designing model architectures, preparing and curating training data, implementing distributed training and data-loading infrastructure, and creating evaluation benchmarks for model quality. The role requires deep learning expertise, experience with Transformers and diffusion models, distributed training and inference on large clusters, and the ability to solve high-impact technical challenges. Experience delivering impactful products or open-source projects is a bonus.

Lead the Ads Signals & Measurement data engineering team across conversion and attribution, measurement foundations, audience onboarding, and identity. Set cross-organizational technical direction, resolve scalable data architecture decisions, mentor engineers, and partner on platform-wide initiatives. The role requires expertise in modern data stacks, advertising technology data flows, privacy and governance, distributed systems, and emerging AI technologies.

Own Talent’s knowledge governance strategy, taxonomy, information architecture, indexing, content lifecycle, and AI-readiness across a federated organization. Build standards, metrics, review rhythms, cross-business alignment, and AI-assisted content workflows. Partner with platform teams, guide business-unit adoption without direct authority, influence the Netflix Knowledge Platform roadmap, onboard additional business units, and establish the team needed to scale the function.