Top Tech Jobs & Startup Jobs in Denver & Boulder, CO

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.

Develop high-quality, performant, accessible consumer-facing experiences for Netflix’s iOS app using Swift and GraphQL. Responsibilities include building maintainable code, automation, documentation, server-driven UI infrastructure, and ad experiences. Collaborate with product managers, designers, and engineering teams to scope projects, refine interfaces, design scalable solutions, and balance business, product, and architectural trade-offs.

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.

Build and ship Android features and infrastructure for Netflix’s global streaming and discovery experiences. Design maintainable, testable software using modern Android technologies, collaborate with product and engineering teams, evaluate technical trade-offs, modernize codebases, and support shared client frameworks. Engineers may work on server-driven UI, ads platforms, SDKs, developer tooling, or high-scale real-time experiences while using automated testing and GenAI development workflows.

Build and own 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, write testable TypeScript and JavaScript code, develop automation, and validate product variants through A/B testing. The role focuses on performance and memory-constrained devices and has measurable customer and business impact.

Leads complex design programs for premium live sports and entertainment broadcasts, managing graphics packages, studio design systems, production schedules, budgets, vendors, and technical playout workflows. Partners with creative, engineering, production, and executive stakeholders while overseeing on-site graphics integration from remote production trucks. Requires deep broadcast operations expertise, strong leadership, and extensive domestic and international travel for year-round live events.

Lead ML technical strategy for Live Ads, designing and deploying forecasting, targeting, bidding, auction, and yield-optimization models. Build and evaluate large-scale production ML systems, create online/offline evaluation frameworks, partner with product to set objectives and trade-offs, and communicate results to stakeholders and leadership.

Lead and grow a senior machine learning and causal inference research team; define long-term research strategy; balance foundational and applied projects; partner cross-functionally to translate research into product impact; build external academic collaborations, publications, and a high-performing research program.