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 data is clean, accurate, and optimized for machine learning models. Monitors, evaluates, and optimizes learning processes to continuously improve high-performance models. Works with other data and analytics professionals to optimize, refine, automate and scale analysis into repeatable analytics solutions and decision support tools.

• Designs and develops machine learning (ML) and deep learning systems.
• Runs machine learning tests and experiments. Trains and retrain systems to prevent drift and optimize results.
• Solves complex problems with multi-layered data sets, extends existing ML frameworks and optimizes existing machine learning libraries.
• Develops Machine Learning apps, implements algorithms, and builds tools to apply ML frameworks.
• Turns unstructured data into useful information by auto-tagging images and text-to-speech conversions.
• Develops ML algorithms to analyze huge volumes of historical data to make predictions.
• Runs tests, performs statistical analysis, and interprets test results.
• Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
• Provides specialized consulting, analytical and technical support.
• Exercises judgment to identify, diagnose, and solve problems within given rules.
• Works independently and regularly handles non-routine situations.
• Broader work or accountabilities may be assigned as needed.

Qualifications:

Foundational level of proficiency:

• Systems Thinking.

Intermediate level of proficiency:

• Mathematics, Statistics & Operations Research.
• Critical thinking.
• Creative reasoning.
• Verbal & written communication skills.
• Collaboration & team skills.
• Analytical and problem solving skills.
• Data driven decision making.

Advanced level of proficiency:

• Computational Thinking and Programming.
• Deep Learning.
• Machine Learning.
• Scaling Models.
• Continuous Integration and Continuous Delivery/Deployment.
• ML algorithm.
• Typically between 5 - 7 years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.
• Deep knowledge and technical proficiency gained through extensive education and business experience.

Salary:

$88,800.00 - $165,600.00

Pay Type:

Salaried

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact.  We strive to help you make an impact from day one – for yourself and our customers.  We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at http://jobs.bmo.com/us/en

BMO is proud to be 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, status as a protected veteran, status as an individual with a disability, or any other legally protected characteristics. We also consider applicants with criminal histories, consistent with applicable federal, state and local law.

BMO is committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation because of a disability for any part of the employment process, please send an e-mail to BMOCareers.Support@bmo.com and let us know the nature of your request and your contact information.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.