Senior Back-end Engineer (Machine Learning) | Uber Direct

About the Role

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.

What You'll Do

- 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.

Basic Qualifications

- 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.

Preferred Qualifications

- 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.

For New York, NY-based roles: The base salary range for this role is USD$202,000 per year - USD$224,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link [](;br>
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](;br>
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.