Position Summary...

What you'll do...

About team:

Walmart’s AI & Data organization is building platform capabilities and enterprise services that accelerate the journey from idea to AI-powered solution safely and cost-effectively for builders across the enterprise. This includes foundational data platforms, ML infrastructure, AI productization, governance, and Associates builder solutions that enable millions of associates, and data practitioners.

We are looking for a Staff Data Scientist to set the technical direction for GenAI, agentic AI, and ML initiatives that accelerate the journey from idea to AI-powered solution across the enterprise — safely, cost-effectively, and at Walmart scale. You will architect production-scale, multi-agent and stateful AI systems on top of our foundational data platforms and ML infrastructure, lead applied research on frontier techniques, evolve our LLMOps and governance capabilities in partnership with platform teams, and mentor data scientists and ML engineers across levels — multiplying the impact of the AI productization and Associates builder solutions that empower millions of Walmart associates and data practitioners.

What you will do

• Set technical direction for GenAI, agentic AI, and AI/ML initiatives across the team; partner with engineering, product, and leadership on multi-quarter roadmaps
• Architect end-to-end, production-scale GenAI and agentic AI systems — including multi-agent orchestration, tool integration, long-term memory, retrieval, evaluation, observability, safety, and cost optimization — using frameworks such as LangChain, LangGraph, or equivalents
• Lead applied research and rapid prototyping on frontier techniques such as advanced reasoning and planning, fine-tuning (SFT, LoRA/QLoRA, DPO, RLHF/RLAIF), distillation, multi-modal models, and emerging agentic patterns
• Partner with platform and infrastructure teams to evolve MLOps and LLMOps capabilities, including distributed training, low-latency serving, evaluation harnesses, monitoring, and governance
• Champion responsible and trustworthy AI: evaluation methodology, red-teaming, guardrails, human-in-the-loop processes, fairness, privacy, and regulatory compliance
• Co-own translation of business problems within the data science discipline into data-driven and mathematical solutions; recommend appropriate methods and tools and demonstrate impact through clear use cases
• Select appropriate modeling techniques for complex problems with large-scale, structured and unstructured data sets (including streaming data and raw text); develop variables and features iteratively in close collaboration with the business
• Design experiments and create test-and-learn frameworks; build continuous, online model learning together with iterative model enhancements
• Develop and apply newer modeling techniques — advanced machine learning algorithms and AutoML — by leveraging the latest trends in ML and AI to train, fine-tune, and apply models to new data sets
• Guide the team on feature engineering, experimentation, and advanced modeling techniques for complex problems with unstructured and multi-source data (e.g., streaming data, raw text, embeddings)
• Identify model evaluation metrics and apply best-practice techniques for testing and tuning to assess accuracy, fit, validity, and robustness for multi-stage models and ensembles
• Deploy models to production; continuously log and track model behavior against defined metrics; identify model parameters that may need modification depending on the scale of deployment
• Write production code using appropriate languages and frameworks; create test cases to validate proposed solution designs; build proofs of concept; deploy software to production servers; contribute documentation, maintain playbooks, and provide timely progress updates
• Drive understanding of priority and SLAs for data work; help identify the most suitable, fit-for-purpose data sources (internal and external) and perform initial data quality checks on extracted data
• Provide recommendations to business stakeholders for complex problems; develop business cases with projected ROI or cost savings; translate business requirements into projects aligned to overall strategy; identify and surface high-value business insights
• Serve as a technical evangelist for the team — represent the team's work in internal forums, tech talks, and architecture reviews across the broader organization
• Build and lead virtual/working groups across organizational boundaries to tackle ambiguous, multi-team problems
• Mentor and grow data scientists and ML engineers across levels through technical coaching, design and code reviews, hiring, and career development; raise the technical bar across the team

What you will bring

• 8+ years of professional experience building and operating large-scale AI/ML systems, with significant recent depth in GenAI and/or agentic AI in production
• Master's or PhD in computer science, machine learning, statistics, mathematics, engineering, or a related quantitative field, or equivalent industry experience
• Demonstrated track record of leading and shipping flagship AI/ML or GenAI products at scale, with measurable business impact
• Expert-level GenAI experience: production RAG at scale, advanced prompt strategies, fine-tuning (SFT, LoRA/QLoRA, DPO), distillation, evaluation, and agentic orchestration patterns
• Deep, hands-on experience designing multi-agent and agentic AI systems using LangChain, LangGraph, or equivalents — including planning, tool-use, long-term memory, and stateful multi-turn workflows
• Proven experience leading LLM/GenAI evaluation and responsible AI efforts: offline and online evaluation, red-teaming, guardrails, fairness, privacy, and compliance with relevant regulations
• Experience setting technical strategy for GenAI/agentic AI initiatives and influencing roadmaps across multiple teams, including partnership with director- and VP-level stakeholders
• Mastery of foundational machine learning, statistics, deep learning, and NLP/LLMs, with strong working knowledge of at least one additional domain (recommendation/ranking, computer vision, time-series, causal inference, or reinforcement learning)
• Deep, hands-on experience with advanced modeling techniques on complex, multi-source data — including unstructured text, streaming data, AutoML, and continuous/online learning
• Expert-level proficiency in Python and modern ML/DL frameworks (PyTorch, TensorFlow, JAX, Hugging Face Transformers)
• Strong background in LLMOps/MLOps: feature stores, model registries, training/serving pipelines, monitoring, drift detection, online experimentation, and governance
• Strong systems thinking — scalability, reliability, latency, cost, and safety tradeoffs in complex AI/ML systems
• Working knowledge of SQL and large-scale data processing tools such as Spark, Hive, BigQuery, or equivalents
• Proven ability to mentor mid-senior individual contributors and grow junior talent into senior roles
• Experience setting and upholding the technical bar across teams — reference architectures, standards, and design review practices
• Excellent written and verbal communication, with the ability to translate complex technical tradeoffs into clear narratives for technical and executive audiences
• Bias for action paired with a rigorous, principled, research-informed approach
• Strong collaborative and ownership-oriented mindset, with a history of inclusive technical leadership and effective cross-functional partnership

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 expert's 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.

Benefits

Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more.

Walmart’s culture sets us apart, and we know being together helps us innovate, learn and grow great careers. This role is based in our Bangalore office for daily work, with the flexibility for associates to manage their personal lives.

Belonging

We aim to create a culture where every associate feels valued for who they are, rooted in respect for the individual. Our goal is to foster a sense of belonging, to create opportunities for all our associates, customers and suppliers, and to be a Walmart for everyone.

At Walmart, our vision is "everyone included." By fostering a workplace culture where everyone is—and feels—included, everyone wins. Our associates and customers reflect the makeup of all 19 countries where we operate. By making Walmart a welcoming place where all people feel like they belong, we’re able to engage associates, strengthen our business, improve our ability to serve customers, and support the communities where we operate.

Equal Opportunity Employer

Walmart, Inc., is an Equal Opportunities 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. That means understanding, respecting and valuing unique styles, experiences, identities, ideas and opinions – while being inclusive of all people.

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Minimum Qualifications:Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 4 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics related field. Option 3: 6 years' experience in an analytics or related field.

Preferred Qualifications...

Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.

Primary Location...

Block- 1, Prestige Tech Pacific Park, Kadubeesanahalli Village, Varthur Hobli , India