MLOps Platform Developer
Posted A month ago
Job Description
A career within Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations in order to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.As part of our Data Science and Machine Learning team, you will design, build, and optimize systems for data collection, storage, access, and analytics at scale. This includes Machine Learning, Deep Learning, and Artificial Intelligence Model Design and Construction, responsible for developing, programming and training the complex networks of algorithms that make up Machine Learning, Deep Learning, and Artificial Intelligence to develop applications and systems. You will work on client engagements related to research and development across a wide range of domains including understanding and improving Machine Learning, Deep Learning, and Artificial Intelligence, addressing bias and fairness in algorithms, embodied and interactive solutions on GCP, Azure and AWS.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 a 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
• Proven experience as an MLOps Engineer or ML Platform Developer.
• Strong proficiency with Vertex AI and Kubeflow pipelines.
• Bachelor's or master's degree in computer science, Engineering, or a related field.
• Solid understanding of machine learning lifecycle and best practices.
• Experience with Google Cloud Platform (GCP).
• Knowledge of data engineering and data pipeline tools (e.g., Apache Beam, Airflow).
• Understanding of data governance and compliance standards.
• Proficiency in Python.
• Familiarity with CI/CD tools and practices.
• Experience with containerization technologies such as Docker and Kubernetes.
• Experience with other MLOps tools and frameworks (e.g., MLflow, TFX).
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana).
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.
PwC BC Region Pay Range Information
The salary range* for this position is $103,000.00 - $137,400.00 - $171,800.00 CAD Annual, plus individuals may be eligible for an annual bonus payment. Actual compensation within the range will be dependent upon your skills, experience, qualifications and geographic location.
*Please note that the salary range for this position is reflected for our British Columbia region. Given our national recruiting approach, we recruit (and may hire) in other regions and therefore the salary range may differ depending on the work location. PwC is committed to competitive compensation and sharing salary ranges in accordance with applicable pa y transparency legislation as they arise.
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
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.
Meaningful work you'll be part of
As a 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
• Proven experience as an MLOps Engineer or ML Platform Developer.
• Strong proficiency with Vertex AI and Kubeflow pipelines.
• Bachelor's or master's degree in computer science, Engineering, or a related field.
• Solid understanding of machine learning lifecycle and best practices.
• Experience with Google Cloud Platform (GCP).
• Knowledge of data engineering and data pipeline tools (e.g., Apache Beam, Airflow).
• Understanding of data governance and compliance standards.
• Proficiency in Python.
• Familiarity with CI/CD tools and practices.
• Experience with containerization technologies such as Docker and Kubernetes.
• Experience with other MLOps tools and frameworks (e.g., MLflow, TFX).
• Experience with monitoring and logging tools (e.g., Prometheus, Grafana).
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.
PwC BC Region Pay Range Information
The salary range* for this position is $103,000.00 - $137,400.00 - $171,800.00 CAD Annual, plus individuals may be eligible for an annual bonus payment. Actual compensation within the range will be dependent upon your skills, experience, qualifications and geographic location.
*Please note that the salary range for this position is reflected for our British Columbia region. Given our national recruiting approach, we recruit (and may hire) in other regions and therefore the salary range may differ depending on the work location. PwC is committed to competitive compensation and sharing salary ranges in accordance with applicable pa y transparency legislation as they arise.
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
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.
About PwC
Industry
Management and ConsultingCompany Size
5001-10,000 employees
Application closing date is 2025-01-05
Current Openings
-
Full Time
-
Full Time
-
Full Time
-
Full Time
-
Full Time
-
Full Time
-
Full Time
-
Full Time
-
Full Time
-
Full Time