Sr. Machine Learning Engineer (Canada - Remote)

Hyatt Hotels Corporation

Canada

Remote

CAD 90,000 - 110,000

Full time

7 days ago
Be an early applicant

Get more replies from employers

Send a job-specific resume in minutes.

Benefits offered by this job

Annual bonus eligibility
Remote work option

Job summary

Hyatt Hotels Corporation seeks a Senior ML Engineer to join our Data Science and Machine Learning group in Canada (remote). You will collaborate with data science, data engineering, and platform teams to translate ML models into production-grade services, utilizing robust MLOps, CI/CD, and scalable infrastructure.

You will design, deploy, and optimize AI services across cloud environments, with a focus on real-time and batch inference, observability, and cost efficiency.

Qualifications

  • 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.
  • 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.

Responsibilities

  • 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.

Skills

Cloud platforms
CI/CD
ML tooling
Mentoring

Education

Master’s degree in Computer Science, Software Engineering, Machine Learning, or related field

Tools

EC2
SageMaker
EKS
Model observability

Job description

Close Inclusive Collection Job Postings Notification

"I joined as a server on the catering staff. Thanks to Hyatt's training and support, I now oversee a brilliant team that helps brings events to life."

Sr. Machine Learning Engineer (Canada - Remote)

Canada

Technology

Professional Staff/Corporate

Full-time

Yearly US Dollar (USD) pay basis

Summary

The Opportunity

Hyatt Hotels Corporation seeks an enthusiastic Senior ML Engineer to join our Data Science and Machine Learning department. In this role, you will be collaborating closely with the broader Data and Analytics team, where you’ll be instrumental in continuing to make Hyatt a leading hospitality company. You will be part of a team that is passionate about our purpose, committed to nurturing curiosity and new skills, and building connections across the organization with colleagues, customers, and guests.

Who We Are

At Hyatt, we believe in the power of belonging and creating a culture of care, where our colleagues become family. Since 1957, our colleagues and our guests have been at the heart of our business and helped Hyatt become one of the best and fastest-growing hospitality brands in the world. Our transformative growth and the addition of new hotels, brands, and business lines can open the door for exciting career and growth opportunities for our colleagues.

As we continue to grow, we never lose sight of what’s most important: People. We turn trips into journeys, encounters into experiences, and jobs into careers.

Why Now?

This is an exciting time to be at Hyatt. We are growing rapidly and are looking for passionate changemakers to be a part of our journey. The hospitality industry is resilient and continues to offer dynamic opportunities for upward mobility, and Hyatt is no exception.

How We Care for Our People

What sets us apart is our purpose—to care for people so they can be their best. Every business decision is made through the lens of our purpose, and it informs how we have and will continue to support each other as members of the Hyatt family. Our care for our colleagues is the key to our success. We’re proud to have earned a place on Fortune’s prestigious 100 Best Companies to Work For® list since 2013. This recognition is a testament to the tremendous way our Hyatt family continues to come together to care for one another, our commitment to a culture of inclusivity, empathy, and respect, and making sure everyone feels like they belong.

We’re proud to offer exceptional corporate benefits which include:

  • Annual allotment of free hotel stays at Hyatt hotels globally
  • A global family assistance policy with paid time off following the birth or adoption of a child as well as financial assistance for adoption
  • Extended Health Benefits for you and your dependents and paid medical days
  • Employer RRSP Matching Contributions
  • Fitness and Wellness Allowance
  • Cell Phone Allowance

Who You Are

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 Role

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.

Responsibilities
  • 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
Qualifications

Experience Required:

  • 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 Preferred

  • 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:

ThesalaryrangeforthispositionisCAD90,000 - CAD110,000.Thispositionisalsoeligibletoearnanannualbonus.

Thefinalpayrate/salaryofferedtothesuccessfulcandidatewilldependonexperience,skilllevelandotherqualificationsfortherole,aswellasthelocationoftheperformanceofwork.Payforthesuccessfulcandidatewillmeetlocalrequirements,includingthelocalminimumwagerate.

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.

Hyatt Regency London - The Churchill | London , ENG , GB

Regional Office - EAME | Multiple Locations

Shared Services Center - Moore | Moore , OK , US

Get your free, confidential resume review.
or drag and drop your file here.
Similar jobs

Similar jobs worth comparing

Senior ML Engineer - Remote Canada, AI Platform & MLOps
Senior ML Engineer - Remote Canada, AI Platform & MLOps

Hyatt • Canada

On-site
CAD 90,000 - 110,000
Annual hotel stays
Flexible work schedule
RRSP matching
+2
Principal Machine Learning Engineer
Principal Machine Learning Engineer

United States Digital Space LLC • Toronto

Hybrid
CAD 154,000 - 232,000
Principal Machine Learning Engineer
Principal Machine Learning Engineer

Equinix • Toronto

On-site
CAD 154,000 - 232,000
Employee Assistance Program
Canada Core Benefits
Principal Machine Learning Engineer
Principal Machine Learning Engineer

Equinix, Inc. • Toronto

On-site
CAD 154,000 - 232,000
Employee Assistance Program
Healthcare coverage
Retirement plans
+1
Machine Learning Engineer
Machine Learning Engineer

Manulife Financial • Toronto

Hybrid
CAD 94,000 - 144,000
Health benefits
Pension plan
Global share ownership plan
+1
Machine Learning Engineer , Amazon Customer Service
Machine Learning Engineer , Amazon Customer Service

Amazon • Vancouver

On-site
CAD 115,000 - 192,000
Health insurance
RRSP
DPSP
+1
Staff Machine Learning Software Engineer
Staff Machine Learning Software Engineer

ODAIA • Toronto

On-site
CAD 150,000 - 190,000
Engineering Manager, Data and ML - (Remote - Canada)
Engineering Manager, Data and ML - (Remote - Canada)

Jobgether • Canada

Remote
CAD 90,000 - 150,000
Remote-first culture
Competitive compensation package
Generous vacation policy
+7
Staff Machine Learning Software Engineer
Staff Machine Learning Software Engineer

RBC • Vancouver

On-site
CAD 180,000 - 230,000
Machine Learning Engineer
Machine Learning Engineer

Altis Technology • Montreal (administrative region)

Hybrid
CAD 90,000 - 120,000
Exposure to complex, enterprise-scale machine learning initiatives
Opportunities with modern ML frameworks and cloud technologies
Collaborative environment that values innovation
+1