Top Tech Jobs & Startup Jobs in Boston, MA

Build full-stack features and infrastructure analytics products to improve Netflix's cloud and AI efficiency. Design frontends (React/TypeScript), backend services/APIs (GraphQL/Node), shape data models, collaborate with analytics and data engineers, and own product direction from design through implementation.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

Lead product strategy and execution for cloud gaming infrastructure, driving roadmaps, end-to-end projects, and infrastructure innovations. Optimize cloud compute, streaming performance, latency, storage, and developer tools to deliver high-quality game streaming. Collaborate cross-functionally, translate performance data into features, and improve developer workflows to enable scalable, performant game streaming experiences.

Lead product strategy and roadmaps for games social platform features (multiplayer, sharing, chat). Drive end-to-end execution for backend systems and partner tooling, align cross-functional stakeholders, use experimentation and UX feedback to iterate, and partner with Trust & Safety, Legal, and Support to ensure a high-quality, trusted social experience.

Lead product for Data Developer and Analytics Experiences, defining strategy, roadmaps, and delivery for SQL/Python authoring, semantic layer, developer tooling, visualization, governance, and GenAI integrations to improve productivity and reuse across Netflix analytics.

Build and maintain performant, accessible consumer-facing experiences for Netflix’s iOS app using Swift and GraphQL. Collaborate with product managers, designers, and engineers to scope projects, refine interfaces, develop shared infrastructure, and make architectural trade-offs. Teams may focus on client foundations, server-driven UI, advertising frameworks, or ad insertion. Responsibilities include writing robust maintainable code, automation, documentation, and supporting high-quality, scalable mobile experiences.

Build and ship Android features and foundational infrastructure for Netflix’s global app. Responsibilities include designing maintainable, testable code; developing shared frameworks and tooling; partnering with product, design, and engineering teams; modernizing Android practices; using automated testing; scoping projects and making technical trade-offs; and applying GenAI tools to improve development workflows.

Design, develop, operate, and improve Netflix’s internet-scale managed compute infrastructure. The role involves building distributed systems and Kubernetes-based services, balancing customer usability with reliability, scalability, and cost efficiency. Responsibilities include collaborating with Product and stakeholders, leading cross-functional infrastructure initiatives, mentoring engineers, maintaining operational excellence, improving incident response and on-call practices, and evaluating emerging cloud and compute technologies.

Design and build performance-focused TV UI architectures for Netflix’s streaming applications across smart TVs, game consoles, and cable boxes. Enable scalable development for engineering teams by improving developer experience, ergonomics, resource management, performance, memory usage, and technology integration. Responsibilities include systems-level architectural thinking, API design, profiling, collaboration with UI, design, platform, and tooling teams, and making thoughtful implementation trade-offs.

Design and implement machine learning and optimization algorithms for Netflix’s ad marketplace. Build, train, and evaluate models using large-scale production data; develop online and offline evaluation frameworks; and partner with product teams to define objectives and trade-offs. Communicate technical decisions and experiment results to diverse stakeholders while providing technical guidance and aligning ML solutions with business goals.