This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
You will drive the development and operations of security services and frameworks that protect Uber’s user-facing products and core platforms. This role is ideal for a strong software engineer with a machine learning background who is excited to apply ML/GenAI techniques to real-world security problems at scale. The security landscape evolves constantly—and with the rise of ML/GenAI and the growing volume of heterogeneous signals (logs, events, graph data, identity signals, endpoints, network telemetry), the attack surface expands just as quickly. You will design and build robust, scalable systems and data pipelines that enable detection, investigation, and automated response—turning noisy telemetry into actionable security insights. You’ll collaborate closely with security leadership and partner engineering teams to embed security-by-design across Uber’s technology stack.
Job Responsibility:
Build ML-powered security systems: Design, develop, and operate software and services that improve Uber’s security posture, with a focus on detection, classification, and risk scoring
Develop backend infrastructure and ETL pipelines: Build reliable data ingestion, transformation, and feature pipelines to support security analytics and machine learning workflows
Productionize ML for security use cases: Help take models from experimentation to deployment—owning performance, scalability, monitoring, and model/data quality in production
Code review and testing: Maintain high engineering standards through design reviews, code reviews, testing, and operational excellence
Cross-functional collaboration: Partner with teams like network operations, incident response, and compliance to ensure cohesive, end-to-end security outcomes
Requirements:
BS/MS in Computer Science or a related field
7+ years of industry experience in a software development environment
Proficiency in one or more of Golang, SQL, Python
Hands-on experience building and operating distributed systems
Hands-on experience with machine learning (e.g., feature engineering, training/evaluation, or deploying models)
Experience leading projects with global, cross-functional stakeholders