Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Build and architect scalable Android client code, UI frameworks, tooling, and server-driven UI architecture using Kotlin, Compose, GraphQL, and related technologies. Establish engineering best practices, automated testing, and modernization strategies; collaborate across client and server teams; influence architecture roadmaps; mentor engineers; and deliver forward-looking technical solutions with minimal supervision. The role supports Netflix experiences across millions of users and thousands of devices.

Lead the vision, strategy, and roadmap for Netflix’s Title Launch Management product portfolio, spanning content ingestion, distribution, launch orchestration, and operational tooling. Manage and develop a team of Product Managers while partnering with Engineering, Operations, Design, Rights, Localization, and other teams. Drive automation, reduce manual intervention and turnaround time, improve launch quality, and translate operational challenges into scalable product investments.

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.

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.

Sets technical direction and architectural coherence across Netflix’s Ads Data Engineering organization. The role guides cross-domain data system decisions, partners with engineering and business leaders, mentors data engineers, shapes platform-wide initiatives, and advances AI-native data engineering. Responsibilities span modern data foundations, ad-tech data flows, privacy and governance, platform migrations, scalable data products, and collaboration with Ads Platform Engineering, Data Science, and Product teams.

Owns analytics datasets and data products for Netflix’s cloud games infrastructure. Builds scalable pipelines, data models, metrics, dashboards, tooling, and self-service assets from massive telemetry data. Partners with infrastructure engineering, data engineering, and data science teams to improve quality of experience, capacity, and utilization insights. Responsibilities include telemetry and logging, visualization, trustworthy documentation, scalable data solutions, and independently prioritizing high-impact investments.

Build and own high-performance UI features for Netflix’s TV application across streaming sticks, smart TVs, and cable boxes. Collaborate with product, design, algorithms, and engineering teams to define experiences, validate product variants through A/B testing, and deliver reliable, testable code. Lead large cross-functional projects while working with TypeScript, JavaScript, React, Redux, Node.js, GraphQL, and proprietary Jest-based automation frameworks.

Lead the creative vision and execution of Netflix Live’s visual design language. Build immersive creative worlds, scalable design systems, and polished broadcast or cinematic deliverables across live events, sports, formats, and genres. Direct and produce 3D assets from modeling through final render, leverage AI and emerging technologies, write creative briefs, guide cross-functional partners, present to senior leadership, and manage multiple productions while mentoring creative teams.

Design and develop scalable analytics tools, dashboards, evaluation frameworks, and observability systems for promotional media and marketing workflows. Partner with machine learning engineers, data scientists, product managers, and business stakeholders to monitor algorithm adoption, pipeline health, performance drift, and SLA adherence. Translate ambiguous creative and quality requirements into measurable objectives, improve recommendation and asset-generation models, and use data insights to guide business decisions.

Build and deploy low-latency machine learning models and inference infrastructure for Netflix’s advertising platform. Develop identity resolution, behavioral and contextual targeting, lookalike expansion, user signals, and audience features at massive scale. Collaborate with science, product, engineering, operations, design, and research teams to productionize models while supporting privacy, governance, security, and advertiser brand safety.