Join Workday: Where Your Workdays Shine Brighter

At Workday, our journey began with a simple conversation over breakfast in a sunny California diner. Our founders envisioned transforming the enterprise software market, and as we grew, it was our unique culture that set us apart. This culture, centered on putting people first, continues to drive our success. Our Workmates believe a healthy, employee-centric, and collaborative environment is key to business success. We care for our people, communities, and the planet, while remaining profitable.

About the Team

Join the dynamic Workday Assistant team! As part of the Employee Experience organization, we enable employers to engage and support their workforce more effectively, making work personal and productive. We're looking for a dedicated Machine Learning Operations Engineer to assist in our strategic mission to meet workers where they are.

About the Role

As a Machine Learning Engineer focused on ML Ops, you will:

• Implement MLOps tools, frameworks, and platforms for ML development, deployment, and governance.
• Create reusable ML workflows for model training, evaluation, deployment, and maintenance.
• Enhance tracking and monitoring of models, experiments, artifacts, and data.
• Collaborate with data engineers and data scientists on feature engineering.
• Quickly diagnose and resolve ML workflow and production issues.

You will apply your creative thinking, analytical, problem-solving, and technical skills to impact thousands of enterprises and millions of people.

Basic Qualifications

• 3+ years of experience with Python in production and ETL settings.
• 2+ years of experience building Data or MLOps pipelines using Python, Airflow, Databricks, or similar cloud-native services.
• 2+ years of experience with AWS, Vertex AI, and Kubernetes.
• 2+ years of experience operationalizing Data Science projects using platforms like Airflow, Kubeflow, AWS SageMaker, Google AI Platform.
• 1+ years of experience building data/ETL pipelines and model training infrastructure, including GPU work.
• 1+ years of experience managing and supporting Docker, Kubernetes, Spark, CI/CD, and GitOps.
• 1+ years of experience with data versioning, ML model management, lifecycle, and reproducibility.

Other Qualifications

• Experience with ML frameworks such as PyTorch, Keras, Transformers, and SKLearn.
• Experience with fine-tuning NLP models and HuggingFace.
• Experience with AWS services, especially EKS.
• 1+ years of experience with MLOps tools like TFX, MLFlow, Kubeflow, Apache Spark.
• Bachelor’s degree in a relevant field (e.g. Computer Science, Mathematics, Engineering). An M.S. or Ph.D. is a plus.

About You

• Highly self-motivated and enjoys delivering production-scale machine learning solutions.
• A collaborative team player with a positive leadership approach.
• Quick learner, detail-oriented, decisive, and thrives in a fast-paced environment.
• Reliable, flexible, and maintains a positive work attitude.

Workday Pay Transparency Statement

The annual base salary ranges for our primary and additional locations are listed below. Compensation varies based on location, with eligibility for the Workday Bonus Plan or role-specific commission/bonus, and annual refresh stock grants. Recruiters will provide details during the hiring process. Compensation offers are based on various factors, including geography, experience, skills, job duties, and business needs. For more details on Workday’s comprehensive benefits, .

Primary Location

CAN.BC.Vancouver

Primary CAN Base Pay Range

$120,000 - $180,000 CAD

Additional CAN Location(s) Base Pay Range

$120,000 - $180,000 CAD

Our Approach to Flexible Work

With Flex Work, we combine the best of both in-person and remote work. This approach helps deepen connections, maintain a strong community, and