Senior Machine Learning Engineer
About The Position
As a Senior Machine Learning Engineer, you will play a critical role in designing, building, and productionizing scalable machine learning and large language model (LLM) solutions that drive our digital-first, customer-centric marketing vision. You will leverage your software engineering expertise to develop robust ML/LLM pipelines, optimize model performance, and ensure seamless integration into production environments. Working closely with AI scientists, cross functional engineers, and marketing teams, you will enable intelligent, real-time customer engagement across omni-channel platforms. 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
- Degree/diploma in Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- 5+ years' hands-on experience in software development, with a strong background in architecting, building and deploying machine learning solutions.
- Past experience with digital marketing domain is highly preferred.
- Strong software engineering skills (git, unit testing, code reviews, containerization with Docker/Kubernetes).
- Proficiency in Python, Spark, modern ML frameworks (PyTorch, Tensorflow, Hugging Face Transformers).
- Advanced working SQL knowledge with scalable data pipelines.
- Practical experience with scalable cloud systems and cloud ML tools (Databricks, GCP, AWS), preferably with Databricks.
- Experience with ML Ops / LLM Ops practices including CI/CD for ML, automated deployment, and model lifecycle management.
- Familiarity with monitoring tools (e.g., MLflow, Prometheus, Grafana) and model governance frameworks.
- Excellent communication skills, with the ability to translate technical solutions into business impact.
Responsibilities
- Build, optimize, and productionize machine learning and large language model pipelines for marketing applications, ensuring reliability, scalability, and maintainability.
- Architect and manage end-to-end ML/LLM Ops workflows, including CI/CD, automated model deployment, monitoring, retraining, and governance.
- Apply best practices in software development (version control, testing, code reviews, modular design) to deliver high-quality, robust ML systems.
- Utilize cloud platforms (Databricks, GCP, AWS) and big data tools (Spark) to process and manage large-scale customer data for model training and inference.
- Implement tools and frameworks for continuous monitoring, performance evaluation, and automated retraining of ML/LLM models in production.
- Work cross-functionally with AI scientists, engineers, and marketing stakeholders to translate business requirements into technical solutions and drive adoption of AI/ML technologies.
- Maintain clear, comprehensive documentation of ML/LLM pipelines, processes, and best practices.
- Mentor junior engineers and contribute to team knowledge sharing.
Benefits
- Competitive salary
- Incentive pay
- Banking benefits
- Benefits program
- Defined benefit pension plan
- Employee share purchase plan
- 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
Senior
