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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # (USA) Senior, Data Scientist - **Company:** Wal-Mart Stores, Inc. - **Location:** Sunnyvale, CA, United States - **Experience:** Expert - **Salary:** $117,000.0 - $234,000.0 - **Contract:** Permanent contract - **Skills:** Adobe Analytics, A/B Testing, Web Accessibility, Artificial Intelligence, Data Analysis, Application Frameworks, Computer Vision, Business Software, Distributed Computing Environment, Information Retrieval, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Scala (Programming Language), Web Content Accessibility Guidelines, Reinforcement Learning, Supervised Learning, Feature Engineering, Large Language Models, Apache Spark, Deep Learning, Model Validation, Generative AI, AI Coding Agents, Agentic-AI, Scikit Learn, Information Technology, Low Latency, Crowd Sourcing, Machine Learning Operations - **Published:** October 28, 2026 - **Apply:** https://dejobs.org/x/x/7FC54157FD244863BB7D34F80A8C737E/job/ ## About the Role * Strong hands-on expertise in Python, machine learning, deep learning, NLP, information retrieval, computer vision, multimodal AI, and model evaluation. * Ability to translate customer and business needs into model designs, experiments, technical requirements, and scalable production solutions; communicate findings and tradeoffs clearly across product, engineering, data, business, and leadership teams. * Experience adapting open-weight models for specific business use cases through model selection, post-training, fine-tuning, and evaluation, including LLM-, vision-, multimodal-, and agent-based systems. * Experience benchmarking models and participating in A/B tests; optimizing training and inference architectures across quality, cost, latency, throughput, scalability, and reliability through techniques such as prompt optimization, custom loss functions, reasoning models, and test-time scaling. * Experience creating high-quality retail training and evaluation data, including dataset sourcing and curation, unsupervised or weakly supervised learning, synthetic-data approaches, and ground-truth development with crowdsourcing and annotation partners. * Experience with distributed training and inference, large-scale model serving, and massively parallel GPU systems; ability to use AI coding assistants effectively and build production agentic AI applications that orchestrate models, tools, and workflows., * 4+ years of experience building machine learning models or developing algorithms for business applications. * Master's or PhD in Computer Science, Electrical Engineering, Machine Learning, Engineering, Robotics, Operations Research, Statistics, Mathematics, or a related quantitative field; or equivalent practical experience. * Experience with LLM post-training and alignment, including supervised fine-tuning, reinforcement learning, RLHF, DPO, or related techniques. * Experience with image or video generation models, multimodal understanding models, or production computer-vision systems. * Experience building, evaluating, and operating LLM- or agent-based systems at production scale., Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications. Option 1- Bachelor's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years' experience in an analytics related field. Option 2- Master's degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field. Option 3 - 5 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. Data science, machine learning, optimization models, Master's degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Using open source frameworks (for example, scikit learn, tensorflow, torch), We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart's accessibility standards and guidelines for supporting an inclusive culture. ## Description What you'll do... About the Team Retail AI Foundations is part of the Retail Intelligence group within Walmart's AI & Data organization. The team develops and deploys Generative AI and machine learning platforms, models, and services across Walmart's highest-impact growth pillars-including AI Shopping, Social Commerce, Walmart Connect advertising, creator experiences, marketing, and rich-media content. Our Applied Science and ML Engineering teams build AI capabilities across Large Language Models (LLMs), image and video generation, and multimodal understanding. We partner with scientists, engineers, product managers, and business leaders to improve experiences for customers, associates, advertisers, and creators, while delivering measurable business outcomes. We are committed to exceeding industry standards through cutting-edge research, strong engineering execution, and responsible AI practices., As a Senior Data Scientist within Retail AI Foundations, you will develop, evaluate, and deploy advanced AI models and algorithms that power Walmart's next-generation customer and business experiences. You will apply applied-science rigor to turn complex customer and business problems into scalable, measurable AI solutions. This role combines hands-on model development with cross-functional influence. You will work directly with ML Engineers, product managers, data teams, and business partners to define success measures, build and validate models, and improve their performance in production. What You'll Do * Build, evaluate, and improve ML and Generative AI models across LLMs, image and video generation, multimodal understanding, and agentic systems. * Develop data and evaluation strategies, including dataset curation, exploratory analysis, feature engineering, error analysis, ground truth, and offline evaluation. * Design and execute model experiments, benchmarking, and A/B tests to measure quality, safety, reliability, latency, scalability, and business impact. * Apply post-training, fine-tuning, retrieval, prompting, and other optimization techniques to improve model performance for production use cases. * Partner with product, engineering, data, and business teams to translate customer and business opportunities into technical requirements, success metrics, and deployable solutions. * Work with ML Engineers to deploy, monitor, and iterate on models in large-scale production environments. * Communicate technical recommendations and model results to stakeholders, while mentoring junior scientists and engineers on rigorous experimentation and responsible AI practices.