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8,103

Ai jobs in Canada

MLOps Platform Developer

PricewaterhouseCoopers International

Toronto
Hybrid
CAD 80,000 - 110,000
30+ days ago
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Bilingual Implementation Associate

Employment Hero

Canada
Remote
CAD 65,000 - 85,000
30+ days ago

Sorter PM 173

Purolator

Truro
On-site
CAD 30,000 - 60,000
30+ days ago

Ingénieur système de maintenance/ Maintenance System Engineer

Keolis North America

Terrebonne
On-site
CAD 90,000 - 120,000
30+ days ago

Billing Analyst

Employment Innovations

Canada
Remote
CAD 60,000 - 80,000
30+ days ago
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Sr UX Researcher I - Bilingual (French/English)

RELX

Quebec
Hybrid
CAD 80,000 - 110,000
30+ days ago

Account Executive - Canada

Employment Hero

Canada
On-site
CAD 60,000 - 90,000
30+ days ago

Senior Revenue Analyst

Solink

Ottawa
Remote
CAD 75,000 - 95,000
30+ days ago
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Director, Brand Design

Opendoor

Vancouver
On-site
CAD 140,000 - 193,000
30+ days ago

Talent Acquisition Specialist

Cohere

Toronto
Hybrid
CAD 50,000 - 70,000
30+ days ago

Sr. Copywriter, Growth

LeadStack

Canada
Remote
CAD 70,000 - 90,000
30+ days ago

Senior Security Engineer

Cohere

Toronto
Hybrid
CAD 125,000 - 150,000
30+ days ago

Software Engineering Associate (open to US or Canada)

Innodata Inc

Toronto
On-site
CAD 100,000 - 125,000
30+ days ago

Senior Platform Product Marketing Manager

EvenUp

Canada
Remote
CAD 80,000 - 120,000
30+ days ago

Retail Representative Vernon

Purolator

Vernon
On-site
CAD 30,000 - 60,000
30+ days ago

Senior AI Calibration Engineer — Prompt Optimization & RAG

Robots and Pencils

Calgary
Hybrid
CAD 100,000 - 130,000
30+ days ago

Licensed Real Estate Agent - Simcoe County

Wahi Real Estate

Central Huron
On-site
CAD 60,000 - 80,000
30+ days ago

Staff Software Engineer, Platform Security

Turo

Toronto
On-site
CAD 132,000 - 165,000
30+ days ago

Global AI/ML Architect — Remote-First, High Impact

Medium

Canada Creek
Hybrid
CAD 100,000 - 140,000
30+ days ago

Senior Backend Engineer

Afresh

Canada
On-site
CAD 162,000 - 198,000
30+ days ago

AI Platform Architect — Scale GenAI at Enterprise

Conga

Southwestern Ontario
Hybrid
CAD 130,000 - 160,000
30+ days ago

AI Engineer: Generative AI & LLMs (RAG)

Bell Canada

Toronto
Hybrid
CAD 80,000 - 100,000
30+ days ago

Backend Engineer II: Scale AI Compute & Kubernetes

Zepl

Northwestern Ontario
On-site
CAD 80,000 - 110,000
30+ days ago

Senior Data Engineering Consultant

Intello Technologies Inc.

Mississauga
On-site
CAD 104,000 - 156,000
30+ days ago

Strategic Agentic AI Architect for Enterprise Platforms

KPMG LLP Canada

Montreal
Hybrid
CAD 100,000 - 130,000
30+ days ago

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MLOps Platform Developer
PricewaterhouseCoopers International
Toronto
Hybrid
CAD 80,000 - 110,000
Full time
30+ days ago

Job summary

A leading professional services firm located in Toronto is seeking an MLOps Platform Developer. You will design and troubleshoot MLOps infrastructure, implement Vertex AI and Kubeflow pipelines, and collaborate with data scientists and engineers. Ideal candidates will have a degree in Computer Science or a related field, strong skills in Vertex AI and Kubeflow, and experience in GCP. The role supports hybrid work and offers competitive compensation and benefits.

Benefits

Competitive compensation package
Inclusive benefits
Flexibility programs
Continuous development environment

Qualifications

  • Proven experience as an MLOps Engineer or ML Platform Developer.
  • Solid understanding of machine learning lifecycle and best practices.
  • Familiarity with containerization technologies.

Responsibilities

  • Design, develop, and troubleshoot MLOps infrastructure.
  • Implement and manage Vertex AI and Kubeflow pipelines.
  • Collaborate with teams to integrate machine learning workflows.

Skills

Vertex AI
Kubeflow
Python
Problem-solving skills
Collaboration
Docker
Kubernetes
Google Cloud Platform (GCP)

Education

Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Tools

CI/CD tools
MLflow
Apache Beam
Airflow
Prometheus
Grafana
Job description

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision‑making and driving business growth.

Meaningful work you’ll be part of

As an MLOps Platform Developer, you’ll work as part of a team of problem solvers, helping to solve business issues, deliver high quality client service and operational efficiency. Responsibilities include but are not limited to:

  • Design, develop, and troubleshoot MLOps infrastructure to support the deployment, monitoring, and management of machine learning and statistical models.
  • Implement and manage Vertex AI and Kubeflow pipelines to automate model training, validation, and deployment processes.
  • Collaborate with data scientists, software engineers, and DevOps teams to integrate machine learning workflows into the broader technology ecosystem.
  • Optimize and troubleshoot machine learning pipelines to ensure high performance and reliability in production environments.
  • Develop and maintain documentation for MLOps processes, tools, and best practices.
  • Provide recommendations and implement solutions for model monitoring and alerting (training‑serving skew, drift detections, performance issues, etc.).
  • Stay up‑to‑date with the latest industry trends and technologies in MLOps and machine learning, especially as it pertains to Vertex AI.
Experiences and skills you’ll use to solve
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Proven experience as an MLOps Engineer or ML Platform Developer.
  • Strong proficiency with Vertex AI and Kubeflow pipelines.
  • Solid understanding of machine learning lifecycle and best practices.
  • Experience with Google Cloud Platform (GCP).
  • Proficiency in Python.
  • Familiarity with CI/CD tools and practices.
  • Strong problem‑solving skills and attention to detail.
  • Excellent communication and collaboration skills.
  • Experience with containerization technologies such as Docker and Kubernetes.
  • Experience with other MLOps tools and frameworks (e.g., MLflow, TFX).
  • Knowledge of data engineering and data pipeline tools (e.g., Apache Beam, Airflow).
  • Understanding of data governance and compliance standards.
  • Experience with monitoring and logging tools (e.g., Prometheus, Grafana).
  • PwC Canada is committed to cultivating an inclusive, hybrid work environment. Exact expectations for your team can be discussed with your interviewer.
Why you’ll love PwC

We’re inspiring and empowering our people to change the world. Powered by the latest technology, you’ll be a part of diverse teams helping public and private clients build trust and deliver sustained outcomes. This meaningful work, and our continuous development environment, will take your career to the next level. We reward your impact, and support your wellbeing, through a competitive compensation package, inclusive benefits and flexibility programs that will help you thrive in work and life. Learn more about our Application Process and Total Rewards Package at: https://jobs-ca.pwc.com/ca/en/life-at-pwc

PwC Canada acknowledges that we work and live across Turtle Island, on the land that is now known as Canada, which are the lands of the ancestral, treaty and unceded territories of the First Nations, Métis and Inuit Peoples. We recognize the systemic racism, colonialism and oppression that Indigenous Peoples have experienced and still go through, and we commit to allyship and solidarity.

At PwC Canada, our most valuable asset is our people and we grow stronger as we learn from one another. We’re committed to creating an equitable and inclusive community of solvers where everyone feels that they truly belong. We understand that experience comes in many forms and building trust in society and solving important problems is only possible if we reflect the mosaic of the society we live in.

We’re committed to providing accommodations throughout the application, interview, and employment process. If you require an accommodation to be at your best, please let us know during the application process.

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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