Hybrid role (2 days/week in office).
We are seeking a highly analytical and technically proficient ML/AI Engineer to join our ARC team. This role is ideal for someone with a strong foundation in mathematics, statistics, and programming, and a passion for applying AI to solve complex financial problems. You will work to develop AI/ML/DS features for enterprise-wide AI products, develop models, optimize strategies, and contribute to the evolution of our AI-powered financial systems.
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.
Turn structured, semi-structured and unstructured data into useful information.
Develop ML/AI algorithms to analyze large volumes of historical data to derive insights, make decisions, and form predictions.
Run tests, perform statistical analysis, and interpret test results.
Contribute to shaping the digital foundations: Hypergraph Scenario Engine and Network-based Methods; Chatbots; Semantic Engine for meaning-based search.
Conduct large-scale analysis to discover patterns and trends by combining different models and algorithms.
Get insights from data (descriptive, attribution).
Perform Topological Data Modeling, Causality, Variable Importance Analysis, Attribution modeling, and Regression.
Qualifications
Master’s or Ph.D. in Mathematics, Statistics, Computer Science, Data Science, Physics, AI, Machine Learning or a related field.
Experience in model development (ML/ data science, AI/GenAI) within financial services or technology sectors.
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.
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.
Salary & Benefits
Salary: $88,800.00 - $165,600.00
Pay Type: Salaried
The above represents BMO Financial Group’s pay range and type. Salaries may vary based on location, skills, experience, education, and qualifications. Salaries for part-time roles will be pro-rated based on hours worked. For commission roles, the listed salary represents the target for the first year. Total compensation may include performance-based incentives, discretionary bonuses, and other perks and rewards. BMO offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. For details, see Total Rewards.
About Us
At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. We strive to create lasting, positive change for our customers, communities and people, and empower growth through collaboration, innovation, and scale.
Equal Opportunity
BMO is an equal employment opportunity employer. We evaluate applicants without regard to race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, transgender status, sexual stereotypes, age, veteran status, disability status, or any other legally protected characteristics. We provide reasonable accommodations for individuals with disabilities and welcome inquiries to BMOCareers.Support@bmo.com.