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Senior Artificial Intelligence / Machine Learning Engineer

BMO US

$122,400 - $228,000
Oct 8, 2025
Chicago, IL, US
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BMO Financial Group is seeking a Senior ML/AI Engineer to develop AI/ML/DS features for enterprise-wide AI products, optimize strategies, and contribute to the evolution of their AI-powered financial systems.

Requirements

  • Proficiency in Python and SQL, TensorFlow, PyTorch, XGBoost, Scikit-learn
  • Strong grasp of Artificial Intelligence and Machine Learning frameworks and stacks.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and CI/CD pipelines is advantageous
  • Experience in model development (ML/ Data Science, AI/GenAI) within financial services or technology sectors
  • Leadership experience driving initiatives related to AI/GenAI/ML assets

Responsibilities

  • Design and develop Machine Learning models (Supervised, Unsupervised, and Reinforcement Learning), AI (Generative models and Agent Orchestration) models, and Deep Learning models (e.g., Neural Networks and autoencoders).
  • Run Machine Learning tests and experiments.
  • Train and retrain systems to prevent drift and optimize results.
  • Solve complex problems with multi-layered data sets, extend existing ML frameworks (Scikit-Learn, XGBoost, Tensorflow) and AI frameworks (Keras, LangChain).
  • Leverage and develop advanced analytics models (network based, forecasting, rules-based), implement said algorithms, and build tools to apply them.
  • Develop ML/AI algorithms to analyze huge volumes of historical data to derive insights, make decisions, and form predictions.
  • Run tests, perform statistical analysis, and interpret test results

Other

  • Master’s or Ph.D. in Mathematics, Statistics, Computer Science, Data Science, Physics, AI, Machine Learning or a related field.
  • Intellectual curiosity and adaptability to emerging AI and quant finance trends.
  • Strong communication skills to explain complex models to non-technical stakeholders.
  • Ability to work independently and collaboratively in a fast-paced, multidisciplinary environment.
  • Attention to detail and a rigorous approach to model validation and testing