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. We are seeking a highly skilled MLOps Platform Developer with extensive experience working with Vertex AI and Kubeflow pipelines. The ideal candidate will be responsible for designing, developing, and providing guidance on MLOps platforms for our clients, ensuring seamless integration and efficient operation of their machine learning models across their environments and teams.

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.

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

The use of artificial intelligence (AI) in recruiting is just getting started, so we know you have questions about how and why we use it. At certain points during our recruiting process, we rely on AI to improve your experience. This could be during resume review or curating personalized job recommendations, asking you clarifying questions via a chatbot or during our interview scheduling to improve your experience. Our use of AI helps ensure we combat bias by evaluating candidates equally and fairly, without seeing identity information, such as your name, or gender for example). AI also helps us better predict successful hires by reviewing all applicants for a role and the relationship between your skills, experience and likely success at PwC Canada. While AI supports parts of our recruitment process, final hiring decisions always involve human review. For more information about our use and protection of your data, please refer to our Privacy Policy (https://www.pwc.com/ca/en/privacy-policy.html). 668287WD