About the Role
As a Staff Software Engineer on the Uber Eats Feed team at Uber, you will be at the forefront of building and scaling Uber's feed products and its underlying platform. The UberEats Feed team is responsible for the personalized, curated experience that customers see when they open the UberEats app. This includes ML-powered recommendations, merchandising systems, dynamic ranking, and content delivery at scale to millions of users. We build resilient, high-throughput services that bring together data, intelligence, and product logic to power real-time, delightful discovery experiences.
What the Candidate Will Do:
- Design and build robust, scalable backend services to support the UberEats Feed experience for millions of users globally.
- Partner with cross-functional teams including product, design, data science, and ML to deliver innovative discovery and personalization experiences.
- Lead large projects end-to-end, including technical design, implementation, and performance optimization.
- Architect efficient data flows, APIs, and storage strategies to support real-time personalization and recommendations.
- Mentor junior engineers and promote best practices in software development, reliability, and architecture.
- Influence the technical roadmap and long-term vision of the Feed team and broader Eats organization.
Basic Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related technical field.
- 8+ years of backend software engineering experience.
- Strong proficiency in at least one backend programming language (e.g., Go, Java, Python, C++).
- Experience designing and deploying scalable microservices and distributed systems.
- Deep understanding of data modeling, APIs, caching, and performance optimization.
- Track record of delivering high-impact, production-grade systems in fast-paced environments.
Preferred Qualifications:
- Master’s degree or higher in Computer Science or a related field.
- Experience working on consumer-facing applications at large scale and low latency.
- Background in search, recommendations, Ads or ML-powered personalization systems is beneficial.
- Experience with technologies such as gRPC, Kafka, Redis, Cassandra, or similar distributed data systems.
- Strong intuition for improving debuggability posture by strategically investing in monitoring and observability initiatives.
- Strong leadership and communication skills with a track record of technical mentorship.
- Passion for building engaging and delightful product experiences for customers.
For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year.
For all US locations, 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 https://jobs.uber.com/en/benefits.
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.
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.