Machine Learning Engineer

Application Deadline:

08/04/2025

Address:

320 S Canal Street

Job Family Group:

Data Analytics & Reporting

We are seeking a Data Scientist with expertise in AI / GenAI, combined with a strong foundation in MLOps. This role supports the development and operationalization of AI solutions across multiple initiatives in BMO corporate audit, in collaboration with enterprise T&O and Data Science functions. You’ll work closely with data scientists, engineers, and cloud teams to ensure AI solutions are scalable, secure, and production-ready. 

Key Responsibilities 

• Design, build, and deploy both traditional ML models and GenAI solutions aligned with business needs. 

• Collaborate with engineering and cloud teams to implement MLOps best practices for model deployment, monitoring, and retraining, as well as GenAI solutions. 

• Enhance data pipelines to ensure clean, accurate, and production-ready data for training and inference. 

• Conduct experiments and evaluate model performance to inform improvements, mitigate drift, and ensure continued relevance in production. 

• Collaborate across environments to align infrastructure, streamline development workflows, and support scalable model deployment. 

• Support governance and compliance processes, including documentation and review and approval processes. 

• Contribute to reusable tools and frameworks that accelerate experimentation and deployment across projects. 

Qualifications 

• 3–5 years of experience in machine learning, including experience with traditional ML, language models (e.g. BERT), and GenAI/LLMs. 

• Proficiency in Python and ML libraries (e.g., scikit-learn, XGBoost, spacy, LangChain, fastapi, flask). 

• Experience with MLOps tools and practices (e.g., AWS - SageMaker, BedRock, Jumpstart, Azure – AI Foundry, OpenAI service, MLflow, CI/CD, containerization). 

• Strong understanding of statistics, model evaluation, and data engineering fundamentals. 

• Excellent communication and collaboration skills across technical and non-technical teams. 

• Strong investigative research skills to systematically explore, analyze, and synthesize information for insight generation and decision support. 

 

Why Join Us 

• Be part of a high-impact initiative advancing the future of AI in audit and compliance—where rapid iteration and document-rich environments drive meaningful innovation. 

• Work with cutting-edge GenAI technologies in a collaborative, fast-paced environment. 

• Help define and scale MLOps practices in a federated model—without being siloed in a dedicated MLOps team. 

 

Researches, builds, and implements scalable artificial intelligence systems capable of learning and making predictions to business requirements. Enhances data pipelines and lakes to ensure d