Job TitleSenior MLOps EngineerThis position follows our Flex & Connect model of 2x per week onsite in Mississauga, ON.SummaryJoin McKesson’s growing AI/ML team and play a critical role in operationalizing machine learning and Generative AI solutions at scale. This role focuses on deploying, standardizing, and maintaining production‑ready ML and agentic AI systems—enabling consistent, reliable, and optimized delivery of data science innovations that support McKesson’s AIM28 strategic initiatives.What You’ll DoLead deployment and operationalization of ML models and GenAI/agentic solutions, ensuring scalability, reliability, and performancePartner with Data Scientists to identify and automate high‑impact model use cases, building end‑to‑end pipelines (CI/CD, monitoring, alerting)Define and enforce standardized deployment patterns and runbooks across teamsOwn KTLO (keep‑the‑lights‑on) operations for ML and GenAI systems including health monitoring, logging, and performance trackingDesign and implement pipelines for batch, real‑time, and event‑driven inferenceEstablish observability frameworks (monitoring, logging, lineage, alerting)Enable deployment of agentic AI solutions using tools such as LangChain, LangGraph, Semantic Kernel, and Databricks toolsEnsure secure deployment of applications with proper access controls (e.G., Okta integration)Drive cost and performance optimization across ML and GenAI workloadsPartner with architecture, compliance, governance, and legal teams to meet enterprise standardsConduct ongoing research into emerging tools and technologies to improve deployment practicesGuide and influence architectural decisions while maintaining clear separation between platform and deployment ownershipWhat You BringStrong experience deploying ML models into production environmentsHands‑on expertise with CI/CD pipelines, monitoring,



and production ML systemsExperience with GenAI or agentic AI frameworks (LangChain, Semantic Kernel, etc.)Knowledge of model observability, drift detection, and operational supportExperience working in scaling or early‑stage ML environmentsProficiency with cloud platforms (AWS, Azure, or GCP)Strong cross‑functional collaboration skills (Data Science, Product, Architecture)Ability to drive standardization, automation, and platform maturityFocus on reliability, scalability, and optimizationMinimum RequirementsDegree or equivalent and typically requires 7+ years of relevant experience.Preferable Skills & ExperienceExperience with Databricks ecosystem (e.G., Databricks Genie)Familiarity with LangChain, LangGraph, or Microsoft Semantic KernelExposure to GenAI cost optimization / FinOps practicesExperience implementing secure enterprise applications (e.G., Okta)Experience in healthcare or regulated environmentsExperience scaling ML/AI capabilities from experimentation to production maturityCompensationOur Base Pay Range for this position$99,100 - $132,100BenefitsWe are proud to offer a competitive compensation package as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. In addition to base pay, other compensation, such as an annual bonus or long‑term incentive opportunities may be offered.Equal Employment OpportunityMcKesson is an Equal Chance Employer. We provide equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category.ContactTo request a reasonable accommodation, please contact us by email at [email protected] (U.S.) or [email protected] (Canada). Resumes or CVs submitted to this email box will not be accepted.#J-18808-Ljbffr

📌 Sr. Machine Learning Ops Engineer - $99,100 - $132,100 A Year (Winnipeg)
🏢 McKesson
📍 Winnipeg