Machine Learning Engineer

Bank of Montreal; Toronto; Hybrid; CAD 82,000 - 155,000; Full time

Job summary

A leading financial institution in Toronto is looking for a highly analytical ML / AI Engineer. The role involves developing machine learning models and analyzing large datasets to derive insights for AI-powered financial systems. Ideal candidates should have a master's or Ph.D. in a relevant field and strong proficiency in Python, SQL, and machine learning frameworks. This position offers a hybrid work environment and a competitive salary range of $82,800 to $154,800.

Qualifications

• Strong proficiency in Python and SQL is required.
• Experience in financial services or technology sectors essential.
• Intellectual curiosity and adaptability to emerging trends is necessary.

Responsibilities

• Design and develop machine learning models for various applications.
• Run tests and perform statistical analysis to interpret results.
• Contribute to shaping digital foundations and analyze large datasets.

Skills

Python

SQL

TensorFlow

PyTorch

XGBoost

scikit-learn

Machine Learning

Artificial Intelligence

Education

Masters or Ph.D. in Mathematics, Statistics, Computer Science, Data Science, Physics, AI, Machine Learning or a related field

Tools

AWS

Azure

GCP

Job description

Application Deadline : 11 / 29 / 2025

Address : 100 King Street West

Job Family Group: Data Analytics & Reporting

This is a Hybrid role (2 days / week in office)

Role Overview

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.

What will you do :

• 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 huge 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 : 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.
• Conduct large-scale analysis of information to discover patterns and trends by combining different models and algorithms.
• Get insights from data (descriptive attribution).
• Perform Topological Data Modeling Causality Variable Importance AnalysisAttribution modeling Regression.

What you need to succeed :

• Masters 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.

Key Skills

• Industrial Maintenance
• Machining
• Mechanical Knowledge
• CNC
• Precision Measuring Instruments
• Schematics
• Maintenance
• Hydraulics
• Plastics Injection Molding
• Programmable Logic Controllers
• Manufacturing
• Troubleshooting

Salary : $82,800.00 - $154,800.00

Pay Type : Salaried