Do what you love. Love what you do.
At Workday, we help the world’s largest organizations adapt to what’s next by bringing finance, HR, and planning into a single enterprise cloud. We work hard, and we’re serious about what we do. But we like to have fun, too. We put people first, celebrate diversity, drive innovation, and do good in the communities where we live and work.
About the Team
Want to join a fast paced engineering team focused on applying cutting edge Machine Learning (ML) technology to build personalized and smart data products? Do you have strong DevOps skills and can’t wait to bring it to the world of ML products? Want to be a part of helping us build the ML platform that radically improves time to market for ML products? Plus, would you like the work life balance and stability of a market leader named in the Best Companies to Work For by Fortune? The Workday ML team offers a unique opportunity with all these! At Workday, the ML team builds services that power our data products across HR, Finance, Planning, Recruiting, Learning, Search, etc.
If you answer YES to some of these qualifications and are looking to expand your knowledge of Machine Learning services, we'd love to meet you. Apply and see if you have what it takes to be part of the revolution of cloud-based, user-friendly enterprise software systems of tomorrow!
About the role
We are looking for a DevOps Engineer who loves building sophisticated and highly automated infrastructure and services to join our Machine Learning Platform team – who bring their bold ideas forward and can immediately make a significant impact. You will partner with Product Manager, Machine Learning Practitioners, and Platform Engineers to help realize the practical requirements around building out and supporting high-availability and scalable infrastructure and its automation. At Workday, we're continually evolving our pipeline and infrastructure; it's a fun place for DevOps!
You have a BS/MS in Computer Science or a related technical field
Building frameworks, automation, and tooling to enable a culture of quality within the organization.
Leveraging technologies like kubernetes/docker to help our developers scale their efforts in creating new and innovative products.
Creating products and services that enable developers to programmatize their interactions with the ML platform
Experience working with private and public clouds (IAAS, GCP, AWS, etc) and capacity management principles.
Experience deploying to and orchestrating containers in production environments (Containers, Kubernetes, Service Mesh and related technologies).
Experience with communication protocols, restful services, service-oriented architecture, distributed systems, and micro-services.
Experience with Infrastructure automation (Terraform, Ansible, etc.), CI/CD pipelines (GIT, Jenkins etc), and configuration management tools( Ansible, Chef etc).
Experience with building a suite of monitoring services.
Strong mission to put pro-active solutions in place to prevent future problems and automate processes/build services such engineers can self-service their operational requirements and enhance productivity.
Passion for creating and maintaining documentation and troubleshooting runbook.
Available for on-call support on a rotating basis.
Team player with excellent communication skills as well as the ability to prioritize multiple tasks in a fast-paced environment.
Machine learning background
Prior experience with enterprise SaaS products
Expertise in secure network design and implementation
Program management experience and familiar with Agile/Scrum /JIRA.
Colorado Equal Pay Statement. Disclosure required by sb19-085 (8-5-20) of the minimum salary compensation for this role to be located in the state of Colorado. Colorado minimum salary $128,700, plus eligible bonuses, equity, and other benefits .