About the Team
We are the ML Frameworks team headquartered in Pleasanton, CA. We enable real time insights across Workday's applications.
Our focus is on the practical application of optimization and machine learning. Our products help the world's largest organizations make strategic decisions about their people and finances.
We are proud of our nimble, startup like culture. We practice quick ideation, agile development, extensive automated testing and continuous deployment.
Every team is a proud service owner, responsible for development, quality, and production support. Do you want to work on leveraging Workday's vast computing resources with its rich and extensive datasets?
To work with world class engineers and facilitate the development of the ML frameworks and products for the Fortune 500? If so, we should chat.
About the Role
Workday is looking for an SDET engineer to join the Machine Learning Framework team. In this role, you will ensure that the quality of our products exceeds the expectations of our customers.
Your expertise in DevOps and automated testing of large-scale distributed systems will help transform the way we support the customers of our Machine Learning and Optimization services.
Support the tools and infrastructure for build, test, release and monitoring, focusing on developer productivity, release velocity, and product quality.
Develop automation code to deploy and maintain systems and applications that run and monitor services in the public cloud.
Maintain an accurate picture of existing server, storage, networking software / hardware and virtual environments to support scaling against various project requirements and production demands.
Work closely with Dev and QA teams to build and support continuous integration and deployment tooling.
Monitor Build and Release pipelines. Follow up with appropriate teams in a timely manner to resolve issues. Analyze and automate issue detection and mitigation to avoid future occurrence.
Build and maintain CI / CD pipeline infrastructure using build and release orchestration tools
Participate in coordination of production deployments, on-call production support and monitoring
Help identify where we can improve on production resiliency, scalability and redundancy. Lead efforts to drive efforts based on metrics and data.
Interpersonal and communication skills and enjoy working across an organization from Development and QA through Operations and Support.
Strong advocate for Infra as Code and always have an eye for Automating Everything
Experience with production support with strong diagnostic and debugging skills
Solid knowledge of build systems such as Jenkins and / or Bamboo
Experience with automation and delivery such as Puppet
Experience with container / virtualization systems such as Docker, Kubernetes
One or more scripting and programming languages (Groovy, Ruby, Bash, Python) and build tools (SBT, Gradle)
Great to have :
Logging systems : ELK / EFK Stack, Splunk
Data visualization tools : Kibana, Wavefront
Application Monitoring systems : Appdynamics, NewRelic, Prometheus, Telegraf
Exposure to AWS
What Excites You
Machine Learning, Scalability, Hybrid cloud, CI / CD, Java / Scala / Go