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Uber's Road Safety and Insurance Engineering teams sit at the intersection of real-world mobility, large-scale data systems, and safety-critical decision making. Our systems process petabytes of telematics, sensor, and behavioral data that help detecting crashes, assess driving risk and ultimately make every trip safer. Every Uber trip, across ridesharing, delivery, and emerging mobility products, is made safer by the systems this role helps build. With #StandForSafety as a company-wide priority, this is a rare opportunity to shape backend platforms that operate at massive scale and have real-world impact.
Job Responsibility
Lead large, cross-team technical initiatives collaborating with multiple platform teams, from early design through production rollout
Builds strategic relationships with internal stakeholders, partner teams and external partners to deliver on organizational goals
Design and evolve backend systems that ingest, process, and analyze high-volume sensor and telematics data
Partner closely with machine learning and data science teams to productionize ML and signal-processing models for crash detection, driving behavior detection etc
Drive architectural decisions for low-latency streaming pipelines, distributed services, and offline/online data processing systems
Anticipate and address scalability, reliability, and data quality challenges 1–2 years ahead, influencing platform direction proactively
Set and role-model engineering best practices around system design, code quality, observability, incident response, and on-call excellence
Mentor Senior engineers and Staff Engineers, raising the technical bar across the org
Represent the org in company-wide technical discussions, design reviews, and architecture forums
Requirements
BS or equivalent in Computer Science, Engineering, Mathematics, or a related field
Proven experience designing and building large-scale distributed systems serving millions of users
Strong computer science fundamentals: data structures, algorithms, system design, and performance optimization
Demonstrated ability to lead complex projects across multiple teams or organizations
Nice to have
10+ years of professional software engineering experience, with significant backend depth
Experience working with telematics, sensor data, time-series data, or signal processing systems
Hands-on experience with streaming and real-time data pipelines (e.g., Kafka-like systems, stream processing frameworks)
Exposure to machine learning systems in production, including model integration, feature pipelines, or ML-powered decision systems
Strong background in scalability engineering, data consistency, and system observability
Track record of influencing architecture and technical direction across multiple teams
What we offer
Bonus program
Equity award
401(k) plan
Various benefits (details at https://jobs.uber.com/en/benefits)