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Search is a primary discovery surface in Uber Eats that drives over a third of our business. We're on a mission to evolve search from a simple query box into an adaptive, intuitive experience that better understands user intent and helps people confidently decide what to order. The Search Experience team owns the presentation layer for Search: how users express intent and how results are displayed, measured, and iterated across global and in-store search. We build rich experiences using embedded web technology inside the Eats iOS/Android apps, with strict performance and reliability requirements. These experiences are powered by backend services and clean contracts that enable rapid iteration. We partner closely with Ranking/Relevance teams (who own retrieval and ML ranking). Our focus is turning their signals into fast, trustworthy, and high-converting user experiences, while modernizing foundations (performance, instrumentation, experimentation, and developer velocity). Natural Language Search (NLS) is a major investment area, and we're building the presentation layer that makes NLS feel transparent, controllable, and reliable.
Job Responsibility:
Lead ambiguous, cross-functional initiatives spanning UX, engineering, and measurement, turning broad goals into milestones, guardrails, and shippable increments
Own meaningful end-to-end slices across the presentation path, including the contracts between client and server and the systems that power them
Set technical direction for performance, reliability, experimentation readiness, and observability across Search presentation surfaces
Reduce recurring failure modes by improving foundations: rollout safety, regression prevention, instrumentation quality, and developer velocity
Partner deeply with PM, Design, UXR, Data Science, and Ranking/Relevance to align on user intent, trust, and measurable outcomes
Multiply the team through mentoring, design reviews, code reviews, and reusable patterns that make others faster
Requirements:
Scale + Reliability: Built and operated consumer-facing products at scale, with strong instincts for latency, availability, and regression risk
Experimentation + Measurement: Comfortable using A/B tests and data to drive decisions
able to define success metrics, guardrails, and measurement plans
End-to-End Ownership: Can drive work across client and server boundaries, including API design, rollout strategy, and production debugging
Product Craft: Experience building high-performance, reliable user-facing (web) experiences
comfortable debugging rendering, networking, and runtime behavior in production
Leadership through Influence: Ability to lead ambiguous, cross-functional projects by creating alignment and momentum without relying on authority
Communication: Strong written and verbal communication
able to turn ambiguity into clear plans and crisp decisions
Engineering Judgment: High bar for quality and pragmatism
knows when to simplify and when a foundational investment is worth it
Nice to have:
Direct experience with Search, Recommendations, Ranking-adjacent systems, or large-scale discovery products
History of successfully leading complex, cross-functional projects and thriving in ambiguity and autonomy
Strong distributed systems understanding and practical experience building highly available, low-latency services at scale
Data-driven approach with comfort digging into metrics and funnels to diagnose drop-offs and validate impact
High bar for product craft: appreciation for how performance and small UX details shape user behavior, trust, and conversion
Excited about the Inspiration and Discovery direction and motivated to build experiences that meaningfully improve how people explore and decide
Interest in NLS and building presentation-layer experiences that make intelligent systems feel transparent and reliable (without needing to build the ML models)