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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr Software Engineer - **Company:** Uber - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Batch Processing, Databases, Data Systems, Distributed Systems, Apache Hive, Machine Learning, MySQL, Redis, Data Streaming, Real Time Systems, Istio, Apache Spark, Caching, Reliability of Systems, Information Technology, Low Latency, Apache Flink, Apache Kafka, Machine Learning Operations, Software Coding, Marketplace, Databricks, Microservices - **Published:** June 27, 2026 - **Apply:** https://dejobs.org/x/x/A51E72B930DC42A5A90E38D29ED0756E/job/ ## About the Role Exceptional Technical Background 1. Computer Science degree or equivalent technical education 2. 4+ years of industry experience with demonstrated exceptional technical impact. 3. Background at leading technology companies known for world-class infrastructure ( Meta, Amazon, Databricks, TikTok, Google, Netflix, Airbnb, or similar scale) Deep Technical Expertise 1. Expert-level experience with large-scale distributed systems, handling millions of QPS or experience on optimization and simulation. 2. Proficiency in real-time streaming or batch processing (e.g., Kafka, Flink, Spark) and low-latency data systems. 3. Advanced knowledge of database technologies (e.g., MySQL, Hive, Redis) and caching strategies. 4. Experience with microservices architecture, service mesh, and observability at scale 5. Exceptional coding skills in Go, Java and python, with experience in high-performance system design. ---- Preferred Qualifications ---- 1. Strong background in real-time system, math, optimization and simulation. 2. Worked on real-time infrastructure serving 100M+ users, or 1M+ QPS, achieved 10x+ performance improvements, and breakthrough technical innovations 3. Fundamental machine learning knowledge 4. Track record of operational excellence: incident management, SLA optimization, and system reliability ## Description We're looking for a highly skilled Senior Engineer to help design and scale the technical solution behind Uber's real-time dynamic pricing systems, which serve millions of riders and drivers worldwide. In this role, you'll design, build and optimize large-scale, low-latency systems that power pricing decisions across Uber's marketplace. You'll work on the product iteration with the platform that handles over 1 million QPS, ensuring pricing is accurate, timely, and resilient in the face of real-world volatility. You'll collaborate closely with engineers across platform, ML modeling, and data to implement performant, reliable, and maintainable services. This is a unique opportunity to tackle technically challenging problems at the intersection of real-time distributed systems, optimization, and ML, while contributing directly to Uber's core platform efficiency and driver earnings. Why This Role Matters You'll be working on the platform that directly affects millions of drivers' livelihoods and riders' experiences every day. Our pricing systems process billions of real-time decisions, balancing marketplace efficiency, driver earnings, and rider satisfaction. You'll have the opportunity to: 1. Solve unique technical challenges at the intersection of real-time optimization and distributed systems 2. Work with cutting-edge pricing algorithms and ML systems that operate at unprecedented scale 3. Shape the technical direction of critical business with direct P&L impact What the Candidate Will Do ---- 1. Partner with Marketplace Product and science teams to build a unified solution for pricing algorithms iterations and marketplace optimization. 2. Collaborate with ML Engineering teams to build the MVP business product and scale model inference and real-time feature serving for pricing decisions 3. Partner with Platform Engineering teams to ensure 99.99% availability for critical pricing systems, and contribute to multi-quarter 'Pricing as a Platform' initiatives to enhance marketplace efficiency, pricing reliability, and developer velocity. 4. 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