Sr. Machine Learning Engineer (Canada - Remote)

· Fitness and Wellness Allowance

As our ideal candidate, you understand the power and purpose of our culture of care, and embody our core values of Empathy, Inclusion, Integrity, Experimentation, Respect, and Wellbeing.

You enjoy working with others, are results-driven, and are looking for a variety of opportunities to develop personally and professionally.

The Machine Learning Engineer partners with data science, data engineering, and platform teams to design, build, and operate scalable AI services.

This role is responsible for translating machine learning models into reliable, production-grade systems through strong infrastructure design, MLOps automation, and performance optimization.

The position also contributes to cross-functional initiatives that advance the organization’s AI platform capabilities.

• Design and implement end-to-end ML systems, including data ingestion, feature processing, model training, and model serving
• Architect and deploy scalable AI services supporting real-time and batch inference use cases
• Build and maintain ML infrastructure across cloud environments (e.g., EC2, EKS, SageMaker, specialized inference hardware)
• Develop and evolve MLOps platforms, including training pipelines, deployment workflows, feature stores, and model observability
• Implement CI/CD and infrastructure-as-code patterns to automate model lifecycle management
• Optimize model training and inference performance for cost, latency, and hardware efficiency
• Monitor production ML systems for accuracy, reliability, and operational health
• Partner cross-functionally with data engineering, architecture, governance, and security teams to ensure compliant and scalable solutions
• Mentor team members on ML engineering, system design, and operational best practices
• Contribute to special initiatives that advance AI platform maturity and engineering standards

• Master’s degree in Computer Science, Software Engineering, Machine Learning, or a related field
• 5+ years of experience building and operating machine learning solutions in cloud environments, with focus on AI services and MLOps foundations
• Demonstrated hands-on experience delivering end-to-end ML systems, spanning model development, deployment, and production infrastructure
• Proficiency with modern ML engineering tooling, including cloud platforms, data pipelines, and CI/CD workflows

• Experience designing and scaling real-time and batch inference systems in production
• Hands-on experience with deep learning frameworks and model optimization for performance and cost
• Experience building or contributing to shared MLOps platforms, feature stores, or ML observability solutions
• Familiarity with cloud security, governance, and compliance standards

The position responsibilities outlined above are in no way to be construed as all-encompassing.

Other duties, responsibilities, and qualifications may be required and/or assigned as necessary.

We welcome you:

Research shows that individuals tend to apply to jobs only if they meet all the listed job qualifications.

Unsure if you check every box, but feeling inspired to enhance your career?

Apply.

We’d love to consider your unique experiences and how you could make Hyatt even better.

We value our relationships with recruitment partners and require that agencies contact us first before submitting any candidates.

Hyatt will not be responsible for any fees and obligations associated with unsolicited submissions unless a formal agreement is in place.

The salary range for this position is CAD90,000 - CAD110,000.

This position is also eligible to earn an annual bonus.

The final pay rate/salary offered to the successful candidate will depend on experience, skill level and other qualifications for the role, as well as the location of the performance of work.

Pay for the successful candidate will meet local requirements, including the local minimum wage rate.

Candidates must be legally authorized to work in Canada at the time of application and throughout their employment.

Proof of eligibility to work in Canada will be required.

Unless otherwise indicated in the job posting, Hyatt does not sponsor employment visas or work permits for this position.

Applications from candidates who do not meet these requirements will not be considered.

Hyatt is committed to providing an inclusive and accessible recruitment experience.

In accordance with applicable human rights and accessibility legislation across Canada, accommodation is available throughout the recruitment and selection process.

If you require accommodation at any stage, please notify Human Resources, and we will work with you to meet your accessibility needs.