Senior Machine Learning Engineer

About the Role

We’re building a relationship-oriented bank for the modern world. We need talented, passionate professionals who are dedicated to doing what’s right for our clients. At CIBC, we embrace your strengths and your ambitions, so you are empowered  team members have what they need to make a meaningful impact and are truly valued for who they are and what they contribute. To learn more about CIBC, please visit

As a Senior Machine Learning Engineer, you will play a critical role in designing, building, and product ionizing 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.

• Develop & Deploy ML/LLM Solutions – Build, optimize, and product ionize machine learning and large language model pipelines for marketing applications, ensuring reliability, scalability, and maintainability.
• ML/LLM Ops Implementation – Architect and manage end‑to‑end ML/LLM Ops workflows, including CI/CD, automated model deployment, monitoring, retraining, and governance.
• Software Engineering Excellence – Apply best practices in software development (version control, testing, code reviews, modular design) to deliver high‑quality, robust ML systems.
• Cloud & Big Data Integration – Utilize cloud platforms (Databricks, GCP, AWS) and big data tools (Spark) to process and manage large‑scale customer data for model training and inference.
• Model Monitoring & Performance Optimization – Implement tools and frameworks for continuous monitoring, performance evaluation, and automated retraining of ML/LLM models in production.
• Collaboration & Partnership – Work cross‑functionally with AI scientists, engineers, and marketing stakeholders to translate business requirements into technical solutions and drive adoption of AI/ML technologies.
• Documentation & Knowledge Sharing – Maintain clear, comprehensive documentation of ML/LLM pipelines, processes, and best practices. Mentor junior engineers and contribute to team knowledge sharing.

• You have a degree/diploma in Bachelor’s or Master’s in Computer Science, Engineering, or a related field, or equivalent experience.
• You have 5+ years’ hands‑on experience in software development, with a strong background in building and deploying machine learning solutions; past experience with the digital marketing domain is highly preferred. Strong software engineering skills (git, unit testing, code reviews, containerization with Docker/Kubernetes).
• You can demonstrate experience and proficiency in Python, Spark, modern ML frameworks (PyTorch, Tensorflow, Hugging Face Transformers). Advanced SQL knowledge with scalable data pipelines is an asset.
• You can demonstrate practical experience with scalable cloud systems and cloud ML tools (Databricks, GCP, AWS), preferably with Databricks and 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.
• You're motivated by collective success. You know that teamwork can transform a good idea into a great one and that an inclusive team that enjoys working together can bring a vision to life.
• You act like an owner. You thrive when you’re empowered to take initiative, go above and beyond, and deliver results.
• Values matter to you. You bring your real self to work and you live our values – trust, teamwork, and accountability.