Software Development Engineer - ML Ops (us Federal)

Workday Workday · Enterprise · USA.VA.Reston

Software Engineer to design, implement, and deliver highly scalable features for Workday's Machine Learning Runtime platform, focusing on microservices that power production ML features. The role involves developing frameworks, automation, and tooling for ML Runtime Inference applications, working with public clouds, and deploying/orchestrating containers in production environments.

What you'd actually do

  1. Developing frameworks, automation, and tooling to foster a culture of efficiency and innovation.
  2. Apply technologies like Kubernetes, Docker, and Python to enhance developer scalability in creating innovative ML Runtime Inference applications.
  3. Implementation and operation of distributed systems and software development including the conception, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components.
  4. Developing products and services that empower developers to streamline their interactions with the ML platform.
  5. Working with public clouds (such as IAAS, AWS, GCP) and applying capacity management principles.

Skills

Required

  • Kubernetes
  • Docker
  • Python
  • distributed systems
  • public clouds
  • Containers
  • Service Mesh
  • ArgoCD
  • infrastructure as code
  • on-call support

Nice to have

  • ML Ops
  • ML Runtime Inference
  • ML platform
  • capacity management
  • TS/SCI w/CI Poly

What the JD emphasized

  • U.S. Federal Government
  • United States citizens
  • security clearance
  • TS/SCI w/CI Poly

Other signals

  • ML Runtime platform
  • Machine Learning Runtime Inference applications
  • ML platform
  • new ML tools