Job Title

Position Summary The role defines strategy, requirements, and delivers scalable ML platforms, operational frameworks, and tooling that power Machine Learning and AI initiatives across the organization. The position collaborates across business and technology functions to ensure reliable model deployment, governance, and performance, while introducing innovative MLOps and supporting DevOps practices that strengthen automation and delivery pipelines. What You''''ll Do Lead the strategy and execution of ML Operations, ML Platform, and Model Lifecycle Management functions, managing resource prioritization to maximize reliability, automation, and operational excellence. Integrate ML engineering, data science, and platform capabilities with business needs to deliver productiongrade ML solutions with measurable impact. Collaborate with senior stakeholders in Operations, Merchandising, Finance, Technology, and Marketing to identify opportunities where improved ML pipelines, platform tooling, or automation can enhance performance, reduce friction, or scale AI solutions enterprisewide. As a subject matter expert in ML systems and operational best practices, oversee model deployment strategies, CI/CD pipelines for ML workflows, monitoring and observability frameworks, and automated retraining processes. Ensure that production models meet standards for performance, reliability, and governance. Build and execute a longterm roadmap to elevate ML operational maturity by researching, piloting, and introducing innovative technologies in orchestration, feature engineering, model serving, and platform automation. Light DevOps responsibilities, including infrastructure automation for ML workloads, containerization best practices, and collaboration with platform engineering, support this mission. Incorporate targeted data engineering activities such as enabling data ingestion, transformation, and movement into MLready environments to ensure that modeling pipelines are supplied with highquality, wellstructured data. Partner with Data Science, Engineering, Architecture, and DevOps leaders across the organization to share best practices, operational standards, and platform technologies, collaborating to advance enterprise ML capabilities. Lead a crossfunctional team of ML engineers, platform engineers, and other specialists to envision, build, test, and deliver robust systems that enable impactful and reliable AI experiences at scale. Qualifications Must Have 46 years of expertise in infrastructure automation to support scalable ML workloads. 46 years of handson experience with container orchestration platforms, including Kubernetes. Proven ability to design and manage multicloud deployments for ML systems. Strong proficiency in ML lifecycle orchestration, including model training, deployment, monitoring, and retraining workflows. Qualifications Nice To Have Experience working with or building on Walmarts Element platform. Pay range: $109,400.00 $150,480.00. Pay will be determined based on relevant experience. Lchelle salariale pour ce poste est de 109400,00 150480,00. La rmunration sera dtermine en fonction de lexprience pertinente. Minimum Qualifications Age 16 or older Preferred Qualifications / EEO Statement Walmart will accommodate the disabilityrelated needs of applicants and associates as required by law. Important note: To support resume screening, interviews and other candidate evaluations, we may use artificial intelligencepowered tools, including internal or thirdparty developed automated decisionmaking tools. For more information, please see Walmart Canada Job Applicant Privacy Notice. Primary Location 1940 Argentia Rd, Mississauga, ON L5N 1P9, Canada Application Process Are you currently a Walmart associate? Please login to your Workday account and use the FindJobs report to apply for this job. FindJobs Seniority Level MidSenior level Employment Type Fulltime Job Function Engineering and Information Technology Industries: Retail, Manufacturing, and Retail Groceries #J-18808-Ljbffr