Job Description

**Position Summary...** **What you'll do...** What You'll Do Develop LLM-powered intelligent experiences that interpret and generate insights from both tabular and unstructured data. Build and optimize personalized Q&A systems using large language models, enabling context-aware responses tailored to user needs. Design and enhance conversational talent recommendation systems, combining autonomous agent architectures with personalized recommendation algorithms. Advance traditional recommendation systems by evolving them from simple ranked lists to multi-topic, interactive experiences that better reflect user intent. Construct multi-agent intelligent workflows that translate natural language inputs into complex, goal-directed task sequences. Collaborate within a highly cross-functional team, including data scientists, machine learning engineers, product managers, and UX designers. Partner with fellow data scientists to design, prototype, and iterate on AI/ML models and system architectures. Work closely with machine learning engineers to deploy, monitor, and optimize scalable AI/ML solutions in production environments. Collaborate with product managers to design intuitive user experiences, define feedback loops, and analyze user telemetry to guide product improvements. Engage in end-to-end AI/ML product development, from ideation to deployment, while continually expanding your technical and product skillset. Follow and help define robust development standards to ensure the creation of trustworthy, safe, and responsible AI systems. Contribute to internal and external AI/ML research through experimentation, whitepapers, and collaboration with the broader AI community. What You'll Bring Proven experience deploying high-risk NLP applications in real-world, production environments-such as those involving regulatory compliance, privacy, safety, or fairness. Demonstrated ability to advance and implement Trustworthy AI and Responsible ML practices, working cross-functionally with engineering, legal, policy, and product stakeholders across a large enterprise. Track record of mentoring and coaching junior data scientists, especially in navigating ambiguous or novel problem spaces. Strong applied machine learning experience, with solid foundational knowledge in statistics, optimization, and deep learning-preferably gained at leading technology companies (e.g., Google, Meta, Microsoft) or AI-first startups. Excellent communication skills with the ability to synthesize complex technical work into accessible insights for executive briefings, research publications, and external presentations. Advanced proficiency in Python and common ML/DS libraries such as NumPy, pandas, scikit-learn, as well as deep learning frameworks like TensorFlow, PyTorch. Experience designing and deploying scalable deep learning systems, including neural network architecture optimization, model distillation, quantization, or on- device inference. Strong understanding of machine learning infrastructure, including experience with Kubeflow, MLflow, Airflow is a plus. Bonus Skills: Hands-on experience with Text-to-SQL or Text-to-Cypher based application, or the design of modern recommender systems. Experience developing or fine-tuning large language models (LLMs), including prompt engineering, retrieval-augmented generation (RAG), or open-weight model customization. Publication history in top-tier ML/NLP conferences such as NeurIPS, ICML, ACL, EMNLP, or ICLR ㅤ ㅤ ㅤ ㅤ ‎ **Minimum Qualifications...** _Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications._ Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 5 years' experience in an analytics related field. Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 3 years' experience in an analytics related field. Option 3: 7 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, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Publications or active peer reviewer in related journals or conference, 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. **Primary Location...** 508 Sw 8Th St, Bentonville, AR 72712, United States of America Walmart and its subsidiaries are committed to maintaining a drug-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment. 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. That means understanding, respecting, and valuing diversity- unique styles, experiences, identities, abilities, ideas and opinions- while being inclusive of all people.

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Full time, Temporary work,

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