About the Role
The Shopping Ranking and Personalization team sits at the center of the Uber Eats shopping experience and is responsible for delivering personalized, relevant, and high-performing content across the Storefront, Cart, Interstitial, and Checkout surfaces. You will lead a team that powers ranking and personalization across core feature areas including storefront carousels, upsells, bundling, add-ons, and other discovery and conversion experiences spanning Storefront, Cart, and Checkout.
In this role, you will own both the user-facing personalization strategy and the underlying ranking platform that enables it. You will be responsible for a ranking service that facilitates scoring and serving decisions at scale, while partnering closely with Data Science and MLE teams to bring state-of-the-art models into production, including Deep Learning, GenAI, and embedding-based approaches. This is a highly cross-functional and high-impact leadership role with direct influence on customer experience, conversion, affordability, and merchandising outcomes.
What the Candidate Will Do:-
Lead and grow a team of engineers responsible for personalization and ranking capabilities across the shopping journey on the Storefront, Cart, and Checkout surfaces.
- Drive execution against high-stakes, highly visible business goals and engineering priorities, ensuring the team delivers reliable, scalable, and measurable impact.
- Own the technical and organizational strategy for the ranking platform, including the services and APIs that generate, orchestrate, and serve ranking decisions across multiple surfaces and feature areas.
- Partner closely with Product, Design, Data Science, MLE, and partner engineering teams to define and deliver experiences across various shopping features.
- Operationalize modern ML capabilities into production systems, helping bridge experimentation and research into robust product experiences.
- Build the platform and architectural foundations that allow other teams to extend, compose with, and integrate into ranking and personalization surfaces in a scalable and maintainable way.
- Establish strong engineering execution practices across roadmap planning, technical design, prioritization, delivery, operational excellence, and incident management.
- Develop engineers and technical leaders on the team through coaching, feedback, and clear growth opportunities.
Basic Qualifications:-
Minimum 3 years of experience managing software engineering teams.
- Minimum 10 years of experience in software engineering.
- Experience leading teams responsible for complex, distributed, production-grade systems.
- Strong technical fluency in machine learning concepts and practical familiarity with ranking systems, recommendation engines, or ML-powered personalization at scale.
- Track record of building and evolving scalable platforms, services, and architectures that enable extensibility and reuse by other teams.
- Experience hiring, developing, and retaining strong engineering talent while building high-performing teams.
Preferred Qualifications:-
Experience leading teams that own personalization, ranking, recommendations, relevance, merchandising systems, or decisioning platforms.
- Experience bringing ML models into large-scale production systems, including model serving, experimentation, monitoring, and iteration loops.
- Familiarity with modern approaches such as deep learning, embedding-based retrieval and ranking, and GenAI-driven personalization or recommendation experiences.
- Experience building platforms that span multiple user journeys or product surfaces rather than one isolated feature area.
- Strong systems thinking with the ability to balance short-term business delivery and long-term platform investment.
Experience working in consumer, marketplace, e-commerce, delivery, or shopping experiences with tight latency and business performance constraints.
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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.
