Staff, Software Engineer - Backend / ML

Staff Software Engineer - Backend / ML

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.

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.

What you'll do:

• 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/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 productionize 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 analysis, and build preventive measures.
• Contribute to long-range technical roadmaps and communicate technical strategy to senior leadership; resolve cross-team technology disagreements through informed discussion and represent the team in org-level architectural decisions. Stay current with industry research and emerging technologies in search, distributed systems, and ML to inform the team's technical direction.
• Work boldly with a sense of urgency — embrace mistakes, learn from them quickly, and drive the team toward success.

What you'll bring:

• 10+ years of experience designing, developing, and shipping production code in large-scale distributed systems.
• Deep expertise in backend development with Java and Spring Boot — strong fundamentals in object-oriented design, concurrency, and performance optimization.
• Proven track record building cloud-native, high-throughput microservices — including RESTful API design, fault tolerance patterns, and horizontal scaling — deployed on Kubernetes.
• Hands-on experience designing and building data and feature pipelines at scale using Apache Spark (including SparkSQL), working with streaming platforms like Kafka, and NoSQL databases like Cassandra.
• Demonstrated ability to technically lead teams of 6–10 engineers — setting architectural direction, mentoring, and raising the quality bar through design and code reviews.
• A disciplined, test-driven approach to development — you're well-versed in testing frameworks (JUnit, Mockito) and bring a genuine commitment to code quality, testability, and documentation.
• Strong communication skills — able to create clarity from ambiguity, articulate technical trade-offs to both engineering peers and non-technical stakeholders, and influence across teams.
• Proficiency in big data processing and analytics using technologies such as Hive, BigQuery, GCP/GCS, or equivalent.
• Familiarity with NoSQL databases (Cassandra, Cosmos DB), distributed caching, and cloud object storage (Azure Blob Storage).
• Track record of refactoring, redesigning, or rewriting existing high-scale applications is a plus — we are actively modernizing our search platform.

Preferred Qualifications:

• Experience with search engines (Solr, Elasticsearch, Vespa) or similar information retrieval systems, including vector search and embedding-based retrieval (e.g., FAISS, ANN indexes), and familiarity with search domain concepts such as query understanding, retrieval strategies, multi-phase ranking, and relevance optimization.
• Background in machine learning — including core concepts (classification, regression, neural networks, transformer-based models, LLMs), hands-on experience with frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost), and an understanding of the full model lifecycle from training through production serving.
• Hands-on work with ML infrastructure in production — including MLOps practices, model serving optimization (dynamic batching, TensorRT, ONNX, quantization), and building training and inference pipelines at scale.
• Proficiency in Python for data engineering, ML prototyping, or production scripting.
• Familiarity with cloud data platforms and orchestration tools such as GCP, BigQuery, and Airflow.

About Walmart Global Tech:

Imagine working in an environment where one line of code can make life easier for hundreds of millions of people. That's what we do at Walmart Global Tech. We're a team of software engineers, data scientists, cybersecurity experts, and service professionals within the world's leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered. We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions, and reimagine the future of retail.

Flexible, hybrid work:

We use a hybrid way of working that is primarily in office coupled with virtual when not onsite. Our campuses serve as a hub to enhance collaboration, bring us together for purpose, and deliver on business needs. This approach helps us make quicker decisions, remove location barriers across our global team, and be more flexible in our personal lives.

Benefits:

Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include 401(k) match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, and much more.

Equal Opportunity Employer:

Walmart, Inc. is an Equal Opportunity Employer – By Choice. We believe we are best equipped to help our associates, customers, and the communities we serve live better when we really know them. The above information has been designed to indicate the general nature and level of work performed in the role. It is not designed to contain or be interpreted as a comprehensive inventory of all responsibilities and qualifications required of employees assigned to this job. The full Job Description can be made available as part of the hiring process.

The annual salary range for this position is $143