Staff, Software Engineer

Walmart Walmart · Retail · SUNNYVALE TECH CORNERS BLDG 6 CA SUNNYVALE

Staff Software Engineer role focused on evolving backend micro-services, data pipelines, and ML-serving infrastructure for Walmart's search platform. The role involves technical leadership, architectural decisions, and collaborating with data scientists to productionize ML models, with a focus on high-throughput, low-latency services and data/feature pipelines.

What you'd actually do

  1. Own technical direction for search micro-services —Core Orchestration & Retrieval, Query-Understanding, Autocomplete, Facet-Navigation, and more.
  2. Design, build and optimize high-throughput, low-latency services, applying best practices around distributed systems, fault-tolerance, and concurrency
  3. Architect complex query patterns with search engines to power relevance.
  4. Design data and feature pipelines within the search ecosystem
  5. Lead discovery and design for medium-to-large initiatives — partnering with product, data science to translate business requirements into scalable technical solutions

Skills

Required

  • 10+ years of experience designing and shipping production code in large-scale distributed systems
  • RESTful API design
  • fault-tolerance
  • horizontal scaling
  • backend development (Java and Spring Boot a plus)
  • object-oriented design fundamentals
  • building data/feature pipelines using streaming/batch techniques
  • Spark
  • Kafka
  • Hive
  • GCP
  • Cassandra
  • technically leading teams
  • setting architectural direction
  • mentoring
  • raising quality bar through code reviews
  • communication skills
  • creating clarity from ambiguity
  • articulating technical trade-offs
  • influencing across teams
  • Familiarity with ML model integration and machine learning ecosystem

Nice to have

  • Java
  • Spring Boot

What the JD emphasized

  • ML-serving infrastructure
  • productionize ML Models
  • ML model integration
  • high-throughput, low-latency services
  • data and feature pipelines

Other signals

  • ML-serving infrastructure
  • productionize ML Models
  • ML model integration