Uber's Growth & Marketing organization needs to solve the critical challenge of moving beyond "one-size-fits-all" marketing by generating billions of personalized messages each month, covering key moments in the user journey across all of Uber's lines of business. This role will work on core backend services that power personalized recommendations across surfaces like Uber Eats, Rides, and more for millions of customers, aiming to maximize engagement and ensure Uber reaches the right user, at the right time, with the right message.
Requirements
- 3+ years of experience in backend or platform software engineering.
- Proficiency in at least one modern backend language (e.g., Go, Java).
- Strong grasp of computer science fundamentals (data structures, algorithms, OOP).
- Experience designing or operating large-scale distributed systems.
- Experience with building or working on recommendation systems or personalization
- Familiarity with machine learning lifecycle, including feature engineering, A/B testing and deploying models to production.
- Experience with real-time data processing and event-driven architectures.
Responsibilities
- Design, build, and operate scalable backend services for large-scale recommendation systems, including candidate generation, real-time content ranking and guardrailing.
- Partner with Applied Scientists to productionize and iterate on ML models that improve the relevance and quality of personalized content for millions of users.
- Collaborate closely with Product and Marketing teams to ship features that have a direct impact on user engagement and business growth.
- Write clean, maintainable code and participate in design reviews, code reviews, and incident responses
Other
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
- Excellent debugging, problem-solving, and performance tuning skills.
