What are the responsibilities and job description for the Staff Software Engineer, Uber Eats Search Experience position at Uber?
About The Role
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.
What You Will Do
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.
What You Will Do
- 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.
- 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.
- 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).
Salary : $232,000 - $258,000