Staff Software Engineer, Home & Cross-retailer Search

Instacart Instacart · Consumer · United States · Remote · Software Engineering

Staff Software Engineer for Instacart's Home & Cross-Retailer Search team, focusing on building and scaling the infrastructure for customer discovery, search, ranking, indexing, and personalization. The role involves defining technical vision, owning architecture, partnering with ML teams, and improving developer velocity. Requires strong backend systems experience, particularly in search, recommendations, or feed-ranking systems.

What you'd actually do

  1. Define and drive the multi-year technical vision for Home and Cross-Retailer Search infrastructure, spanning retrieval, ranking, indexing, and personalization at scale.
  2. Own the architecture of Instacart's cross-retailer search platform, ensuring correctness, freshness, and low latency as catalog and query volume grows.
  3. Own Home feed ranking and content strategy, retailer selection, and personalized recommendations driven by real-time and batch ML signals.
  4. Partner with ML Platform and Applied Science to productionize ranking models and improve experimentation infrastructure - A/B testing, interleaving, and offline eval
  5. Accelerate developer velocity across the sub-pillar: reduce time-to-production, build reusable components, and make it easy for product teams to experiment with minimal platform friction.

Skills

Required

  • 10+ years of software engineering experience
  • track record of leading large-scale distributed systems in production
  • technical lead or architect on cross-team, multi-quarter initiatives
  • Deep expertise in backend systems: high-throughput APIs, data pipelines, caching strategies, and storage systems.
  • Experience building or scaling search, recommendations, or feed-ranking systems at significant traffic volume
  • Strong command of system design principles: reliability, fault tolerance, observability, graceful degradation
  • Proficiency in one or more of: Ruby, Go, Python, Java, or similar backend languages
  • Strong communication skills

Nice to have

  • Experience at a marketplace or e-commerce platform with complex catalog, inventory, or fulfillment constraints
  • Familiarity with ML serving infrastructure, feature stores, and online/offline evaluation frameworks
  • Experience with real-time data pipelines (Kafka, Flink, Spark Streaming) and search indexing at scale (Elasticsearch, Solr, OpenSearch)
  • Track record of improving developer productivity and platform health: reducing p99 latency, improving cost efficiency and cutting incident rates.
  • Prior work on personalization systems using collaborative filtering, contextual bandits, or session-based signals

What the JD emphasized

  • productionize ranking models
  • offline eval
  • low latency
  • real-time and batch ML signals
  • significant traffic volume

Other signals

  • productionize ranking models
  • personalization at scale
  • search across thousands of retailers and items
  • customer intent across platforms
  • ML signals