McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.

Job Title

Senior MLOps Engineer

This position follows our Flex & Connect model of 2x per week onsite in Mississauga, ON.

Summary

Join 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 Do

Lead deployment and operationalization of ML models and GenAI/agentic solutions, ensuring scalability, reliability, and performance
Partner 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 teams
Own KTLO (keep-the-lights-on) operations for ML and GenAI systems including health monitoring, logging, and performance tracking
Design and implement pipelines for batch, real-time, and event-driven inference
Establish observability frameworks (monitoring, logging, lineage, alerting)
Enable deployment of agentic AI solutions using tools such as LangChain, LangGraph, Semantic Kernel, and Databricks tools
Ensure secure deployment of applications with proper access controls (e.g., Okta integration)
Drive cost and performance optimization across ML and GenAI workloads
Partner with architecture, compliance, governance, and legal teams to meet enterprise standards
Conduct ongoing research into emerging tools and technologies to improve deployment practices
Guide and influence architectural decisions while maintaining clear separation between platform and deployment ownership

What You Bring

Strong experience deploying ML models into production environments
Hands-on expertise with CI/CD pipelines, monitoring, and production ML systems
Experience with GenAI or agentic AI frameworks (LangChain, Semantic Kernel, etc.)
Knowledge of model observability, drift detection, and operational support
Experience working in scaling or early-stage ML environments
Proficiency with cloud platforms (AWS, Azure, or GCP)
Strong cross-functional collaboration skills (Data Science, Product, Architecture)
Ability to drive standardization, automation, and platform maturity
Focus on reliability, scalability, and optimization

Minimum Requirements

Degree or equivalent and typically requires 7+ years of relevant experience.

Preferable Skills & Experience

Experience with Databricks ecosystem (e.g., Databricks Genie)
Familiarity with LangChain, LangGraph, or Microsoft Semantic Kernel
Exposure to GenAI cost optimization / FinOps practices
Experience implementing secure enterprise applications (e.g., Okta)
Experience in healthcare or regulated environments
Experience scaling ML/AI capabilities from experimentation to production maturity

We are proud to offer a competitive compensation package at McKesson 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. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

Our Base Pay Range for this position

$99,100 - $132,100

McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:

McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.

McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.

McKesson job postings are posted on our career site: careers.mckesson.com.

McKesson is an Equal Opportunity Employer

McKesson provides 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. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.

McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) Disability_Accommodation@McKesson.com or (Canada) Accessibility@mckesson.ca. Resumes or CVs submitted to this email box will not be accepted.

Join us at McKesson!

Sr. Machine Learning Ops Engineer

McKesson

Job Description