Base: $168,000 - $252,000 cad; bonus/equity: not s...
On-site
Design and implementation of high-throughput microservices
Kubeflow, kubernetes (eks/gke)
Infrastructure as code (terraform)
We build ML capabilities into our products, and you would be building part of the next generation of Workday technology
Job Summary
We build ML capabilities into our products, and you would be building part of the next generation of Workday technology.
You will apply modern MLOps, CloudOps, and data engineering stacks to enable development, training, deployment, and lifecycle management of a variety of ML capabilities.
We will challenge you to apply your best creative thinking, analysis, problem-solving, and technical abilities to make an impact on thousands of enterprises and millions of people.
Matching Summary
We build ML capabilities into our products, and you would be building part of the next generation of Workday technology.
Salary
Base: $168,000 - $252,000 CAD; Bonus/Equity: Not specified; Benefits: Not specified
Skills & Requirements
Must-have
design and implementation of high-throughput microservices
Kubeflow, Kubernetes (EKS/GKE)
Infrastructure as Code (Terraform)
Python, Go, and infrastructure-as-code tools
design and build software solutions for data
build MLOps platform using Kubeflow, Kubernetes
cloud engineering and security best practices
Nice-to-have
support emerging Agentic AI systems
LangChain and LangSmith is preferred
leadership or mentoring experience
large-scale ML data pipelines and data lakes
think across layers of the ML stack
Key Requirements
6 or more years of validated industry experience
Bachelor’s and/or Master’s degree in Computer Science or Computer Engineering
Deep understanding of cloud computing, cloud infrastructure, and distributed systems
experience with AWS and GCP
Experience running and maintaining Kubernetes clusters in production