BMO Financial Group is seeking an 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 by solving complex financial problems.
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.
- Perform Topological Data Modeling, Causality, Variable Importance Analysis, Attribution modeling, Regression.
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.
- Contribute to shaping the digital foundations: (Hypergraph) Scenario Engine and Network based Methods: graph-based modeling tool that maps relationships between entities and simulates cascading scenarios; Chatbots (i.e., Distribution); Semantic Engine: AI layer that enables meaning-based search as opposed to keyword search.
Other
- This role is Hybrid (2 days/week in office)
- 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.
