Sr. Machine Learning Ops Engineer
$99.1k - $132.1k per yearMCD McKesson Canada Corporation / La Corporation McKesson Canada
Senior MLOps Engineer
Flex & Connect model - 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.
Responsibilities
- 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.
Qualifications
- 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.
Compensation
Base Pay Range: $99,100 - $132,100
In addition to base pay, other compensation, such as an annual bonus or long‑term incentive opportunities may be offered.
Equal Opportunity Statement
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) View email address on ca.talent.com or (Canada) View email address on ca.talent.com. Resumes or CVs submitted to this email box will not be accepted.
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