Top Tech Jobs & Startup Jobs in Seattle, WA

Develop and optimize statistical, mathematical programming, and machine learning models for Uber’s dynamic pricing systems. Analyze marketplace data, design experimentation and causal inference methods, identify algorithm improvements, and deploy solutions with Product, Engineering, and Operations. Build diagnostic tools, logging infrastructure, and marketplace metrics while translating complex analyses into actionable strategies for business leadership.

Owns Uber’s US immigration program, ensuring employment-based immigration compliance, regulatory readiness, stakeholder support, vendor performance, and operational efficiency. Partners with HR, Talent Acquisition, business leaders, and global mobility teams; monitors legislative changes; manages complex immigration escalations, projects, metrics, billing, training, and continuous improvement initiatives.

Owns end-to-end Oracle HCM Cloud Payroll functionality, including configuration, maintenance, optimization, troubleshooting, and operational support. Partners with HR, Payroll, and Operations stakeholders to translate requirements into system enhancements. Supports quarterly releases, UAT, production readiness, root-cause analysis, process automation, and integration impact assessment across Payroll, Time and Labor, and Absence Management.

Lead architecture and evolution of an enterprise vulnerability management platform. Design risk-based vulnerability management systems, automate remediation, integrate security scanning into development and infrastructure workflows, and apply AI/ML to vulnerability triage and remediation. Establish governance, analyze complex vulnerabilities, guide risk decisions, mentor engineers, and collaborate across IT, product, compliance, and operations teams.

Leads Uber’s remote assistance product for autonomous vehicle operations. Owns strategy, roadmap, operator tooling, escalation workflows, partner integrations, metrics, safety guardrails, and launch readiness across markets and vehicle platforms. Collaborates with engineering, autonomy, operations, safety, legal, policy, and external partners to build reliable human-in-the-loop systems, improve intervention quality, and scale commercial AV deployments.

Develop data-driven insights, machine learning and optimization models, experiments, metrics, and diagnostic tools for Uber Direct’s global logistics products. Collaborate with product, engineering, and operations teams to identify growth opportunities, prioritize initiatives, improve production systems, and influence leadership through clear technical communication. The role requires leading complex projects from concept through production and working with large-scale datasets.

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.

Serves as a technical anchor for Uber’s foundational infrastructure. Designs and builds globally scalable orchestration, monitoring, and platform systems; drives cloud and host infrastructure initiatives; improves availability, performance, security, and resiliency; mentors engineers; establishes architectural standards; and leads large-scale projects across their full lifecycle.

Designs and scales network security systems, real-time algorithms, and automated defenses against bot attacks and DDoS threats. Processes network telemetry using streaming and machine learning technologies, automates cloud and edge security controls with Terraform, improves monitoring and resilience, responds to incidents, conducts technical reviews, develops runbooks, and mentors engineers.

Build and launch scalable distributed systems and AI-powered products for Uber’s consumer incentives business. Own machine learning projects end to end, including scoping, offline evaluation, experimentation, production deployment, algorithm tuning, and post-launch maintenance. Collaborate with product, operations, and data science stakeholders while optimizing consumer experiences and business outcomes across grocery and food verticals.