Machine Learning Developer (New or Recent Graduate)

Bank of Montreal; Toronto; On-site; CAD 56,000 - 120,000; Full time

Benefits offered by this job

Health insurance

Tuition reimbursement

Accident and life insurance

Retirement savings plans

Job summary

Bank of Montreal is seeking a Machine Learning Developer in Toronto to design, develop, test, and deploy machine learning applications. The role emphasizes building scalable, cloud-native solutions and collaborating with cross-functional teams.

The ideal candidate has 1–3 years of experience in ML, strong Python skills, and familiarity with AWS services such as Lambda, API Gateway, S3, and SageMaker. This on-site role offers salaried compensation and opportunities to work across a modern tech

Qualifications

• 1-3 years of relevant experience in ML, software development, or internships.
• Strong foundation in ML algorithms, data structures, and software engineering principles.
• Experience with Python and AWS cloud technologies, including serverless architectures.

Responsibilities

• Design, develop, test, and deploy ML solutions addressing business needs.
• Translate requirements into scalable technical specifications and implementations.
• Develop production-ready Python code and support end-to-end SDLC.

Skills

Python

AWS

Machine Learning

Education

Bachelor's degree in Computer Science or related field

Tools

SageMaker

Lambda

API Gateway

S3

IAM

Job description

Application Deadline: 09/12/2026 Address: 33 Dundas Street West Job Family Group: Technology BMO is seeking a Machine Learning Developer to join our team in Toronto. This role is ideal for an early-career professional with a strong foundation in Machine Learning, Python development, and AWS cloud technologies who is passionate about building intelligent, scalable solutions that solve real business challenges.

As a Machine Learning Developer, you will contribute to the design, development, testing, and deployment of machine learning applications and cloud-based solutions. You will work with cross-functional teams to translate business requirements into technical solutions, develop production-ready code, and support the end-to-end software development lifecycle. The successful candidate will have a strong understanding of machine learning algorithms, data structures, software engineering principles, and cloud-native development. Experience developing user-facing applications, serverless functions, and machine learning models through professional experience, internships, university projects, or graduate-level research is highly valued.

Key Responsibilities

• Design, develop, test, and implement machine learning solutions that address business needs.
• Translate user and business requirements into technical specifications and scalable solutions.
• Develop and maintain applications using Python and modern software engineering practices.
• Build, deploy, and support machine learning models in cloud environments, primarily AWS.
• Develop and integrate serverless applications using AWS services such as Lambda, API Gateway, S3, and related cloud technologies.
• Support user interface development and integration with machine learning-powered applications.
• Apply knowledge of machine learning algorithms, model evaluation techniques, feature engineering, and data processing.
• Participate in model deployment, monitoring, troubleshooting, and performance optimization.
• Ensure code and configurations adhere to security, logging, performance, and operational standards.
• Perform root cause analysis, troubleshooting, and ongoing maintenance of applications and services.
• Follow release management processes, version control, and CI/CD practices.
• Evaluate emerging technologies and recommend solutions that improve performance, scalability, and user experience.
• Collaborate with product, engineering, and business teams to deliver high-quality technology solutions.
• Take measured risks while protecting the bank by applying BMO's Risk Management Framework and adhering to all applicable policies, standards, and regulatory requirements.

Technical Skills

• Python Strong programming ability using Python for application development, data processing, and machine learning implementations. Experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or similar.
• AWS Cloud Experience developing or deploying solutions within AWS environments. Understanding of serverless architectures and services such as AWS Lambda, API Gateway, S3, IAM, CloudWatch, and SageMaker.
• Machine Learning Strong foundation in supervised and unsupervised learning algorithms. Understanding of model training, evaluation, feature engineering, optimization, and deployment best practices. Knowledge of AI/ML concepts gained through professional experience, university projects, research initiatives, or graduate studies.

Qualifications

Qualifications Approximately 1-3 years of relevant experience, including: Professional work experience; and/or Relevant co-op placements, internships, university projects, research initiatives, or graduate-level (MBA/Master's) projects focused on machine learning, AI, software engineering, or analytics. Post-secondary degree in Computer Science, Software Engineering, Data Science, Mathematics, Engineering, AI, Machine Learning, or a related discipline. Strong understanding of machine learning algorithms and statistical modeling concepts. Experience developing applications using Python. Exposure to AWS cloud technologies and serverless architectures. Understanding of software engineering principles, testing methodologies, and the software development lifecycle. Experience working with source control tools such as Git. Strong analytical, problem-solving, and debugging skills. Effective verbal and written communication skills.

Preferred

Preferred Experience with AWS SageMaker or other machine learning deployment platforms. Experience building user-facing applications, dashboards, or UI components. Experience with APIs, microservices, and cloud-native architectures. Familiarity with CI/CD pipelines and MLOps practices. Experience working in Agile delivery environments. Master's degree or MBA with AI, Analytics, Data Science, or Technology-focused projects.

Salary: $55,500.00 - $120,000.00

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.

• health insurance
• tuition reimbursement
• accident and life insurance
• retirement savings plans

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 https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

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. BMO is a leading bank driven by a single purpose: to Boldly Grow the Good in business and life. Everywhere we do business, we’re focused on building, investing and transforming how we work to drive performance and continue growing the good.