Vanguard Canada

www.vanguard.ca

1 Job

53 Employees

About the Company

Putting investors first since 1975:

We sell high-quality investment products at the lowest possible price. This is the core of our investment philosophy because we think it's essential to your investment success.

Unique structure:
Vanguard was founded on a simple but revolutionary idea: that an investment company should be run for the sole benefit of its investors.
At Vanguard, we don't have any outside owners, so we don't need to worry about a stock price or about generating profits for outside owners. This helps us keep costs low, so more of your money stays in your pocket--where it belongs.

A pioneer in the industry:
30 million investors worldwide trust us with over $7 trillion of their savings. Together we're changing the way the world invests.

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Terms: https://www.vanguard.ca/en/website-terms-of-use

Listed Jobs

Company Name: Vanguard Canada
Job Title: Senior AI/ML Engineer
Job Description: **Job Title:** Senior AI/ML Engineer **Role Summary:** Design, deploy, and optimize scalable AI/ML systems to enable enterprise-wide model experimentation, deployment, and monitoring. **Expectations:** Deep technical expertise in building production-grade ML infrastructure and driving innovation through data-driven solutions. **Key Responsibilities:** Architect and implement scalable ML pipelines and MLOps frameworks for model deployment, monitoring, and lifecycle management. Collaborate with cross-functional teams to align technical strategies with business objectives. Ensure data integrity, resolve pipeline quality issues, and conduct root cause analysis. Implement model monitoring systems for data/model drift detection, alerting, and resolution. Design A/B testing and validation strategies to evaluate model performance and impact. Translate business requirements into scalable AI/ML solutions and anticipate ambiguity in data or requirements. **Required Skills:** Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with cloud platforms (AWS SageMaker) and containerization/orchestration tools (Kubernetes, Docker). Strong coding practices in testing, version control (Git), and security. Knowledge of cloud-based ML system design, CI/CD, and MLOps lifecycle management. Excellent communication skills for technical-business collaboration. **Required Education & Certifications:** Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred). 8+ years in ML engineering, data engineering, and MLOps, including production ML system design and cloud-based pipeline implementation.