Senior, Software Engineer

Position Summary...

What you'll do...

Personalization team at Walmart is dedicated to the mission of knowing our customers better and making it frictionless and faster for them to get what they want while building a trusted partnership with Walmart. We help bring a seamless experience to our customers irrespective of how and where they engage with us – while shopping online or picking groceries at stores. We thrive to provide each customer with a journey tailored to their individual needs, preferences and routines. We operate at the intersection of huge Walmart assortment, millions of customers, thousands of stores and Walmart associates - a multi-layer multi-objective problem space which has a unique impact on Global customer base and powers assisted AI for our associates.

The Personalization team consists of big data geeks, application engineers, scientists and product visionaries all working together to design, prototype and build technology-driven products and experiences that will change the future landscape of e-commerce. We are focused on building an intelligent system that will enable 1:1 personalized customer experience, from finding the product to delivering it to the customer. We are building state-of-the-art probabilistic models and engineering marvels to serve our customer needs by leveraging cutting edge machine learning, deep learning, reinforcement learning, natural language processing, entity-relationship extraction and knowledge representation. This will span many markets, business models and form factors; therefore, we are looking for scientists and engineers who will bring not only an abundance of experiences in technologies, but an abundant curiosity to innovate.

About Team:

Our team works closely with our US stores and eCommerce business to better serve customers by empowering team members, stores, and merchants with technological innovation. From groceries and entertainment to sporting goods and crafts, Walmart U.S. offers an extensive selection that our customers value, whether they shop online at Walmart.com, through one of our mobile apps, or in-store. Focus areas include customers, stores and employees, in-store service, merchant tools, merchant data science, and search and personalization.

What you'll do:

• Design, build, and deploy large-scale, production-grade ML systems, including deep learning models, real-time inference services, and end-to-end ML pipelines for our generative shopping agents.
• Implement advanced techniques like Retrieval-Augmented Generation (RAG) to provide agents with a comprehensive understanding of long-term customer history, preferences, and intent, as well as short-term session context.
• Champion the use of multimodal data (text, images, user behavior, contextual signals) to power hyper-personalized recommendations, product discovery, and proactive customer engagement.
• Participate in medium- to large-scale, complex, cross-functional projects by reviewing project, product and business requirements; translating requirements into technical solutions; gathering requested information (for example, design documents, product requirement); designing robust and scalable architectures; writing and developing code; conducting unit testing; communicating status and issues to team members and stakeholders; collaborating with cross functional teams; troubleshooting open issues and bug-fixes; enhancing design to prevent re-occurrences of defects; ensuring on-time delivery.

What you'll bring:

• Proven expertise in building and deploying production-grade ML solutions at scale, preferably in e-commerce, search, or recommendation systems.
• Hands-on experience with generative AI, including LLMs, RAG systems, and autonomous agent frameworks.
• Proficiency in Python and relevant ML frameworks (e.g., PyTorch, TensorFlow).
• Deep understanding of ML engineering principles, including data pipelines, model training, and serving infrastructure.
• Familiarity with vector databases, knowledge graphs, and semantic search techniques for efficient memory management and context retrieval.
• Proficient with event driven architecture using Kafka.
• Advanced knowledge of complex software design, distributed system design, design patterns, data structures and algorithms.
• Working knowledge in container and cloud native technologies – Kubernetes, Docker.
• Experience with CI/CD tool