Software Engineer - Backend​/ML

Position Summary…

As a Staff Software Engineer
, you’ll be a technical leader who defines the direction for and evolves the backend microservices, data pipelines
, and ML‑serving infrastructure that power search at massive scale. You’ll lead a team of 6–10 engineers, set the technical vision for critical systems, create clarity from ambiguity on complex cross‑functional initiatives, and drive the quality bar across the team. You’ll spend your days writing and reviewing code, leading design discussions, and making the architectural decisions that shape the next generation of Walmart Search.

Your work will shape how hundreds of millions of customers discover products every day.

We’re in an active phase of platform modernization — redesigning and refactoring core systems. If you want to build, not just maintain, this is the right time to join.

The eCommerce Search engineering team owns the end‑to‑end technology stack that powers product search and discovery across Walmart’s global eCommerce channels, backed by microservices, large‑scale data and feature pipelines, search engines, and ML model serving infrastructure. We handle millions of queries per day, and every improvement to our systems directly impacts how customers find what they need. Our systems tackle an advanced set of problems in the search domain:

• Query & Intent Understanding — Query classification, product type prediction, intent recognition, and sequence tagging using classical ML, NLP, and deep learning techniques.
• Autocomplete — Real‑time query suggestions at low‑latency, high‑throughput scale.
• Retrieval & Search Execution — Complex query construction, faceted navigation, semantic and vector‑based retrieval, and result orchestration across search engines.
• Multi‑phase Ranking — ML‑powered ranking models that optimize for customer satisfaction and business outcomes across multiple ranking stages, using learn‑to‑rank and neural models.
• Data & Feature Pipelines — Large‑scale pipelines that feed search indices, feature stores, and analytics platforms.

• Define the technical direction and drive the architecture for mission‑critical search microservices — spanning Core Orchestration, Query Understanding, Autocomplete, Facet & Navigation, Ranking, and more.
• Design, build, and optimize high‑throughput, low‑latency backend services, applying best practices around distributed systems, fault tolerance, horizontal scalability, concurrency, and performance tuning.
• Design and build high‑scale data and feature pipelines that process data through transformation and aggregation layers into downstream data stores, search indices, and feature stores.
• Architect complex query patterns and integrations with search engines to power relevance, ranking, and retrieval at scale.
• Lead discovery and design phases for medium‑to‑large initiatives — partnering with product management, data science, and UX to translate business requirements into scalable technical solutions; build cross‑functional alignment, drive proof‑of‑concepts, and validate ideas through prototypes.
• Design and run A/B experiments to validate search improvements; use data‑driven analysis and continuous monitoring to measure the impact on customer engagement and business metrics.
• Technically lead a team of 6–10 engineers, including collaboration with offshore and distributed team members — providing architectural guidance, conducting design and code reviews, identifying and removing blockers, and setting the quality bar for the team.
• Mentor and grow engineers across experience levels; drive a culture of engineering excellence through knowledge‑sharing, disciplined testing practices, and thoughtful documentation.
• Collaborate with data scientists to product ionize ML models for ranking and query understanding; contribute to MLOps practices, feature store development, and model serving optimization for latency and throughput in production.
• Build and maintain observability, monitoring, and alerting for search services; participate in on‑call rotations and own the reliability of Search platform services in production — troubleshoot issues with urgency, perform root cause…