Staff Software Engineer, Uber Eats Search Experience

Uber Uber · Consumer · Sunnyvale, CA · Engineering

Staff Software Engineer role at Uber Eats focused on the presentation layer of Search, driving user intent understanding and result display. This role involves leading cross-functional initiatives, owning end-to-end system slices, and setting technical direction for performance, reliability, and observability. The focus is on building user experiences powered by backend services and modernizing foundations, with a significant investment in Natural Language Search presentation.

What you'd actually do

  1. Lead ambiguous, cross-functional initiatives spanning UX, engineering, and measurement, turning broad goals into milestones, guardrails, and shippable increments.
  2. Own meaningful end-to-end slices across the presentation path, including the contracts between client and server and the systems that power them.
  3. Set technical direction for performance, reliability, experimentation readiness, and observability across Search presentation surfaces.
  4. Reduce recurring failure modes by improving foundations: rollout safety, regression prevention, instrumentation quality, and developer velocity.
  5. Partner deeply with PM, Design, UXR, Data Science, and Ranking/Relevance to align on user intent, trust, and measurable outcomes.

Skills

Required

  • Built and operated consumer-facing products at scale, with strong instincts for latency, availability, and regression risk.
  • Comfortable using A/B tests and data to drive decisions; able to define success metrics, guardrails, and measurement plans.
  • Can drive work across client and server boundaries, including API design, rollout strategy, and production debugging.
  • Experience building high-performance, reliable user-facing (web) experiences; comfortable debugging rendering, networking, and runtime behavior in production.
  • Ability to lead ambiguous, cross-functional projects by creating alignment and momentum without relying on authority.
  • Strong written and verbal communication; able to turn ambiguity into clear plans and crisp decisions.
  • 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).

What the JD emphasized

  • Scale + Reliability
  • Experimentation + Measurement
  • End-to-End Ownership
  • Product Craft
  • Leadership through Influence
  • Communication
  • Engineering Judgment
  • Search
  • Recommendations
  • Ranking-adjacent systems
  • large-scale discovery products
  • performance
  • reliability
  • experimentation readiness
  • observability
  • low-latency services