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 distributed systems, public clouds, and container orchestration in production environments. It also includes researching and evaluating new ML tools with reliability and scale in mind.

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
  • software development
  • public clouds
  • capacity management
  • container orchestration
  • Service Mesh
  • ArgoCD
  • infrastructure as code

Nice to have

  • TS/SCI w/CI Poly

What the JD emphasized

  • mandates that all Workday personnel working on the contracts be United States citizens
  • U.S. Federal Government
  • security clearance

Other signals

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