Top Tech Jobs & Startup Jobs in Seattle, WA

Provides technical leadership for enterprise security engineering across endpoints, infrastructure, enterprise applications, and cloud environments. Designs and scales security platforms, automated workflows, endpoint protection, EDR, application controls, system hardening, posture management, and zero-trust capabilities across macOS, Windows, and Linux. Partners with engineering teams to reduce attack surfaces, improve threat detection and prevention, and deliver security-by-default solutions.

Manages complex employee data transactions and lifecycle events, resolves Tier 2 HR escalations, audits data quality, supports HRIS enhancements and UAT, analyzes case trends, and partners with Payroll, IT, vendors, and HR teams to improve processes, compliance, self-service content, and employee experience.

Lead the technical strategy and development of machine learning solutions for Uber’s homepage personalization, including sequential recommendation, intent-aware ranking, LLM-based systems, and agentic AI. Partner with product teams to improve engagement and business outcomes, influence technical direction across teams, and mentor machine learning engineers.

Own and evolve Uber’s developer platform infrastructure for code hosting, code review, code search, and SubmitQueue. Design and maintain Go-based tooling, lead projects through production rollout, establish testing and monitoring standards, track engineering KPIs, support incident response, and improve developer experience across a large monorepo. The role also includes mentoring engineers and collaborating with cross-functional stakeholders.

Design, develop, and productionize machine learning models and pricing algorithms for Uber’s large-scale, real-time marketplace systems. The role focuses on deep learning, causal modeling, reinforcement learning, optimization, and online serving at high volume. Responsibilities include collaborating with engineers, product managers, and scientists, shaping technical direction, solving complex marketplace problems, mentoring junior engineers, and monitoring ML solutions across offline and online environments.

Own Uber’s Android build platform across Bazel, Starlark rules, toolchains, dependency management, remote caching, remote execution, and CI. Improve build speed, reliability, cost, diagnostics, and test selection across a large monorepo. Lead platform migrations, upgrades, observability, incident response, technical standards, and cross-team initiatives while mentoring engineers and setting the Android build roadmap.

Design, develop, and maintain backend software, distributed infrastructure, and data pipelines at scale. Own the software lifecycle from design through production support, including testing, monitoring, incident management, and performance improvements. Collaborate with Product, Data Science, and Operations to translate ambiguous requirements into reliable system designs. Contribute to code reviews, engineering best practices, technical debt reduction, and team development.

Lead the technical strategy, architecture, development, and productionization of large-scale machine learning and pricing systems for Uber’s real-time marketplace. Develop deep learning, causal, reinforcement learning, optimization, and algorithmic pricing solutions serving billions of trips. Mentor engineers, influence cross-team technical direction, communicate with executives, and deliver high-impact systems for millions of drivers.

Lead software engineering projects for Uber’s Autonomous Mobility & Delivery team. Develop strategic roadmaps, technical designs, scalable backend services, and products supporting autonomous vehicle rideshare experiences. Collaborate across product, design, business, legal, operations, and external engineering teams to deliver reliable systems, improve KPIs, and future-proof Uber’s technology stack for autonomous vehicle use cases.

Develop Android features and platform capabilities for Uber’s autonomous mobility products. Lead technical projects from inception through deployment, collaborate with product, data science, and operations teams, and make trade-offs across performance, quality, and delivery speed. Establish testing, monitoring, and alerting standards, manage complex incidents, improve engineering velocity, and deliver high-quality customer-facing mobile experiences at global scale.