Position Summary... What you'll do... 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. About Team: 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.
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Job Type
Full-time
Career Level
Mid Level