Machine Learning Engineer, Enterprise MLOps
About The Position
As a Machine Learning Engineer on the AI Infrastructure & ML Ops team, you'll play a key role in advancing our enterprise machine learning platform. You'll design, build, and maintain robust MLOps workflows, automate pipelines for data ingestion, training, validation, and deployment, and ensure our processes are compliant and audit-ready. You'll collaborate closely with developers, technology teams, and product owners to integrate machine learning solutions into production environments, ensuring reproducibility and traceability throughout the ML lifecycle. Your expertise will help drive enhancements across our platform, and you'll actively contribute to a culture of experimentation, continuous improvement, and knowledge sharing. As part of a collaborative and inclusive team, you'll mentor peers and support junior members, helping us stay at the forefront of emerging ML tools and techniques. At CIBC we enable the work environment most optimal for you to thrive in your role. Details on your work arrangement (proportion of on-site and remote work) will be discussed at the time of your interview.
Requirements
- 5+ years of hands-on experience in Python, CI/CD, Databricks, Azure, MLOps
- Familiarity with Kubernetes, Git, and machine learning frameworks
- Degree/diploma in Computer Science, Software Engineering, or a related field
- Work effectively with cross-functional teams, communicating complex technical concepts clearly to both technical and non-technical stakeholders.
- Ensure that solutions adhere to governance policies, regulatory requirements, and audit standards.
- Support team growth by mentoring peers, participating in code reviews, and contributing to team documentation.
- Bring your real self to work, and you live our values - trust, teamwork, and accountability.
Responsibilities
- Design, build, test, and enhance machine learning components, CI/CD pipelines, and end-to-end MLOps workflows for data ingestion, training, validation, and deployment.
- Implement compliant workflows with approval gates, automated monitoring, alerts, and audit-ready processes to ensure reliability and regulatory alignment.
- Work closely with data engineers, DevOps, developers, and product owners to seamlessly integrate ML pipelines into production systems and align engineering deliverables with requirements.
- Package models, manage deployment environments, and ensure solutions meet governance policies such as Model Risk Management (MRM) and Compliance.
- Stay current with emerging ML tools and techniques, proactively identify opportunities for improvement, and drive enhancements across the MLOps platform.
- Participate in code reviews, contribute to team documentation, share best practices, and mentor peers and junior team members.
Benefits
- competitive salary
- incentive pay
- banking benefits
- a benefits program
- defined benefit pension plan
- an employee share purchase plan
- a vacation offering
- wellbeing support
- MomentMakers, our social, points-based recognition program
- Purpose Day; a paid day off dedicated for you to use to invest in your growth and development
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Associate degree
