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Uber Direct is the white-label delivery engine of Uber, empowering enterprise retailers and local businesses to reach their customers in minutes by leveraging our world-class logistics network. You will build the high-scale APIs, merchant dashboards, and real-time operational tools that bridge the digital and physical worlds for millions of global deliveries. In this role, your work will directly define the future of B2B logistics, turning the "last mile" into a competitive advantage for some of the world's most recognized retail, grocery, and pharmacy brands.
Job Responsibility:
Design and Scale APIs: Lead the development of high-performance public-facing APIs and internal microservices that power the integration between global merchants and Uber’s logistics engine
Solve High-Scale Challenges: Work alongside world-class engineers to derive elegant solutions for complex, distributed systems problems involving high-throughput data and low-latency requirements
Integrate Intelligent Systems: Collaborate with data scientists to integrate machine learning models into production back-end services, ensuring seamless real-time execution
Own Operational Excellence: Take full end-to-end ownership of the reliability, performance, and monitoring of the services you build, ensuring they meet Uber’s rigorous production standards
Drive Quality Metrics: Engineer backend solutions that directly move the needle on core business KPIs, including Completion Rate, On-Time Rate, and Defect Rate through optimized routing and prediction logic
Requirements:
Bachelor's degree in Computer Science, or related technical field, or equivalent practical experience
5+ years of experience as a Back-end Engineer
Demonstrated success shipping production-grade applications using Go (Golang) and Python
Strong experience with distributed systems and microservices architecture at scale
Nice to have:
Proven track record in designing and implementing large-scale, high-performance systems with a focus on concurrency and low-latency
ML in Production: Proven experience training, deploying, and maintaining Machine Learning models within a production environment
Predictive Modeling: Specific experience building or integrating prediction models (e.g., ETA predictions, demand forecasting, or churn modeling)
Big Data Tech: Strong background in data processing and analytics tools such as Hive, Spark, or Kafka
MLOps: Familiarity with ML orchestration tools and CI/CD pipelines tailored for model deployment
Complexity Management: Highly comfortable dealing with the intersection of systemic complexity and data-driven decision-making
Leadership: Demonstrated leadership skills, with experience in mentoring and guiding junior engineers on both backend and ML best practices
What we offer:
Eligible to participate in Uber's bonus program
May be offered an equity award & other types of comp
All full-time employees are eligible to participate in a 401(k) plan