Top Tech Jobs & Startup Jobs in Seattle, WA

Lead design and implementation of gameplay and engine systems on Linux platforms. Mentor engineers, define technical specs, manage Linux infrastructure, optimize performance and security, integrate art, maintain documentation, support live services and mobile (iOS/Android) ports, and coordinate cross-team standards and tooling.

Design, build, and operate scalable, fault-tolerant distributed data infrastructure and platform tooling. Collaborate cross-functionally to architect high-impact systems, contribute to library and platform development, and improve deployment, control, and observability for large-scale data systems.

Design, build, and operate scalable, resilient distributed systems for Netflix's Open Connect CDN. Develop cloud services, steering algorithms, deployment automation, data pipelines, and operational tooling to optimize quality-of-experience, hardware utilization, and cost efficiency while enabling real-time adaptation and reliable production operations.

Lead content design for Netflix Live experiences (sports and events). Create content strategy, craft microcopy and voice, design experiments, partner with designers and product managers, use data and consumer insights to iterate, and evolve globalizable language systems and guidelines.

Lead quality strategy and testing for the iOS Games SDK. Design and implement automated tests, build supporting tools and infrastructure, debug SDK issues, perform manual testing for hard-to-automate features, create test games and samples, and analyze operational data to improve test stability and developer experience.

Lead ML initiatives to improve Sales productivity and automation: define roadmap, design and deploy production ML models and AI agents, build measurement pipelines with analytics engineers, iterate from performance and seller feedback, and act as senior technical partner across product, engineering, and Sales to drive measurable revenue impact.

Lead and grow a backend engineering team building high-scale, low-latency consumer authorization platforms. Provide technical vision, partner with product, security, and data teams, balance short-term needs with long-term strategy, and hire, mentor, and retain diverse engineering talent.

Design and implement ad measurement metrics, perform deep-dive analyses, build reporting and automated pipelines, create visualizations, and provide actionable insights to improve advertiser measurement and platform health.

Design and build scalable training platform infrastructure for large distributed ML model training. Improve performance, reliability, and cost-effectiveness of training jobs. Build APIs/UX for ML engineers, diagnose GPU/communication/memory bottlenecks, and implement observability, fault tolerance, and on-call practices while partnering with ML researchers and infrastructure teams.

Build and maintain scalable batch and real-time data pipelines, model data to power analytics and ML, and operate distributed data systems. Collaborate with business, engineering, and data science teams to ensure data quality, documentation, and debugging while adopting new technologies and working in an ambiguous, fast-changing environment.