Software Development Engineer - Ml Ops (us Federal)
Workday
Mclean, VA, United States
Primary location base pyy range: $137,000 usd - $2...
Fully remote
Kubernetes, docker, python
Ml runtime inference applications
Distributed systems and software development
Develop frameworks, automation, and tooling to enhance developer scalability in creating innovative ML Runtime Inference applications using technologies like Kubernetes, Docker, and Python
Job Summary
Develop frameworks, automation, and tooling to enhance developer scalability in creating innovative ML Runtime Inference applications using technologies like Kubernetes, Docker, and Python.
Implement and operate distributed systems and software development, including the conception, design, programming, testing, and bug fixing for applications and frameworks.
Empower developers to streamline interactions with the ML platform by developing products and services, working with public clouds, and deploying/orchestrating containers in production.
Matching Summary
Develop frameworks, automation, and tooling to enhance developer scalability in creating innovative ML Runtime Inference applications using technologies like Kubernetes, Docker, and Python.
Salary
Primary Location Base Pay Range: $137,000 USD - $205,400 USD; Additional US Location(s) Base Pay Range: $123,900 USD - $222,000 USD; Bonus/Equity: May be eligible for Workday Bonus Plan or role-specific commission/bonus, annual refresh stock grants; Benefits: Comprehensive benefits package
Skills & Requirements
Must-have
Kubernetes, Docker, Python
ML Runtime Inference applications
Distributed systems and software development
Public clouds (AWS, GCP)
Containers, Kubernetes, Service Mesh, ArgoCD
Infrastructure as code
DevOps pipelines for ML runtime
Nice-to-have
Curious minds and courageous collaborators
Sun-drenched optimism and drive
Integrity, empathy, and shared enthusiasm
Machine learning background
Enterprise SaaS products
Leading or mentoring team members
Key Requirements
5+ years DevOps experience (Senior)
3+ years DevOps experience (Intermediate)
Infrastructure automation, building CI/CD pipelines