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Job TitleSr. Manager, MLOps Engineering
SummaryLead the design and execution of McKesson's MLOps strategy to enable scalable, secure, and efficient machine learning operations. This role drives innovation, governance, and collaboration across data science and engineering teams to deliver impactful AI solutions in healthcare.
What You'll Do- Lead, mentor, and develop a high-performing MLOps engineering team, fostering a collaborative, innovative, and accountable culture aligned with organizational goals.
- Define and drive the end-to-end MLOps lifecycle, including model development, CI/CD, testing, deployment, monitoring, retraining, and governance.
- Architect and maintain scalable, secure, and cost-efficient ML infrastructure using cloud-native platforms (e.g., Azure ML, AKS, ADF, Databricks; AWS/Google Cloud Platform as needed).
- Build and optimize automated pipelines and tools for model training, deployment, observability, and incident response to improve operational reliability and reduce manual effort.
- Partner with data scientists, software engineers, product teams, and platform groups to deliver effective, repeatable, and well-governed MLOps workflows.
- Establish and enforce best practices for model versioning, experiment tracking, data lineage, reproducibility, and model lifecycle documentation.
- Implement and maintain robust monitoring, logging, and alerting systems to track model performance, data drift, system health, and infrastructure metrics.
- Ensure compliance with Responsible AI standards, security protocols, and regulatory requirements, collaborating with legal and risk teams.
- Oversee cloud resource allocation, budgeting, and cost optimization across ML workloads in partnership with finance and procurement.
- Maintain comprehensive documentation, SOPs, and governance frameworks to support audits and ensure consistent and transparent MLOps practices.
- Stay current with evolving MLOps trends, tools, and best practices, evaluating and integrating relevant innovations to enhance the platform.
What You Bring- Proven experience leading MLOps or ML engineering teams in enterprise environments.
- Expertise in cloud-native ML platforms (Azure ML, Databricks, AKS; AWS/Google Cloud Platform optional).
- Strong knowledge of CI/CD for ML, containerization (Docker), orchestration (Kubernetes), and ML observability tools.
- Solid understanding of model governance, Responsible AI principles, and compliance frameworks.
- Excellent leadership, stakeholder management, and communication skills.
Minimum Requirements- Degree or equivalent experience. Typically requires 9+ years of professional
experience and 1+ years of supervisory and/or management experience.
Preferable Skills & Experience- Experience with healthcare data compliance (HIPAA, PHI).
- Familiarity with ML monitoring tools (e.g., MLflow, EvidentlyAI).
- Knowledge of cost optimization strategies for cloud ML workloads.
- Advanced degree in Computer Science, Data Engineering, or related field.
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$163,800 - $273,000
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McKesson job postings are posted on our career site: careers.mckesson.com.
McKesson is an Equal Opportunity EmployerMcKesson 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.
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