Software Development Engineer - ML Ops (US Federal)
Core
Design, implement, and deliver highly scalable features for the Machine Learning Runtime platform, powering ML inference applications in production for U.S. federal agencies.
Role type
Software Development Engineer - ML Ops (US Federal)
Builds
Microservices and infrastructure for Workday Machine Learning features
Domain
U.S. Federal Government / Cloud Infrastructure / Machine Learning Operations
Deliverable
production ML models
Required skills
Python, Kubernetes, Docker, Terraform, CI/CD pipeline design, distributed systems, system design, infrastructure automation, monitoring services
Preferred skills
Machine learning background, RESTful services, service-oriented architecture, Grafana, ArgoCD, Git, Jenkins, microservices
Technologies
Kubernetes, Docker, Python, Terraform, ArgoCD, Jenkins, Git, Grafana, AWS, GCP
Responsibilities
Develop frameworks and automation tooling for efficiency; implement and operate distributed systems; deploy and orchestrate containers in production; own features end-to-end including infrastructure as code; research and prototype new ML tools; resolve operational issues and automate processes.
Seniority
Mid-level, hands-on IC