Senior Machine Learning Engineer, Specialist

Vanguard; Toronto; Hybrid; CAD 90,000 - 120,000; Full time

Job summary

A leading financial services organization in Toronto is seeking an experienced Machine Learning Engineer to develop and optimize data pipelines and MLOps for AI/ML models. The ideal candidate has over 6 years of relevant experience, strong proficiency in Python and AWS services, and a commitment to advancing machine learning technology. This position offers a hybrid work model and visa sponsorship.

Benefits

Visa sponsorship

Hybrid work model

Professional development opportunities

Qualifications

• 6+ years of relevant experience in data engineering or machine learning engineering.
• Minimum 3 years of hands-on experience building ETL pipelines using AWS services.
• Proficient in Python and familiar with key machine learning frameworks and libraries.

Responsibilities

• Design, develop, and optimize complex data pipelines using machine learning best practices.
• Develop and implement robust MLOps pipeline for AI/ML models in production.
• Conduct exploratory data analysis and collaborate with data scientists to validate datasets.

Skills

Python

AWS services

Machine Learning frameworks

ETL pipeline development

Data engineering

Education

Bachelor’s degree in a relevant field

Master’s degree

Tools

AWS SageMaker

Machine Learning Development Lifecycle (MDLC)

Job description

Supports and performs the development and programming of machine learning integrated software algorithms to structure, analyze, and leverage data in a production environment.

Core Responsibilities

Design, develop, and optimize complex data pipelines using machine learning engineering best practices to ensure scalability, efficiency, and reliability.

Develop and implement robust MLOps pipeline to support the deployment, monitoring, and lifecycle management of AI / ML models in production environments.

Integrate and maintain data and model pipelines, proactively diagnosing data quality issues and documenting assumptions.

Collaborate closely with data scientists to validate model-ready datasets and ensure thorough, accurate feature documentation.

Conduct exploratory data analysis and discovery on raw data sources, incorporating business context to support model development.

Track data lineage and perform root cause analysis during early-stage exploration or issue resolution.

Partner with internal stakeholders to understand business processes and translate them into scalable analytical solutions.

Develop and maintain model monitoring scripts, investigate alerts, and coordinate timely resolutions.

Act as a subject matter expert in machine learning engineering on cross-functional teams, contributing to high-impact initiatives.

Stay current with advancements in AI / ML and evaluate their applicability to business challenges.

Qualifications :

Bachelor’s degree in a relevant field required; Master’s degree preferred.

6+ years of relevant experience in data engineering or machine learning engineering.

Minimum 3 years of hands-on experience building ETL pipelines using AWS services

Proven experience developing and implementing MLOps pipeline for deploying, monitoring, and managing AI / ML models in production.

Proficient in Python and familiar with key machine learning frameworks and libraries.

Strong understanding of cloud technologies and AI / ML platforms like AWS SageMaker.

Solid grasp of software engineering principles, including design patterns, testing, security, and version control.

Knowledge of the Machine Learning Development Lifecycle (MDLC) and best practices.

Experience designing and implementing end-to-end machine learning pipelines and solution architectures.

Special Factors

Sponsorship

Vanguard is offering visa sponsorship for this position.

About Vanguard

At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.