Workday

1 week ago

Software Development Engineer - ML Ops (US Federal)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 27 minutes agoStatus: Live

Job Summary

Design and deliver scalable capabilities for the Machine Learning Runtime platform supporting Workday Government. Build and operate distributed microservices that power ML inference, partnering with data scientists and ML engineers. Develop automation, frameworks, and developer-facing tools, deploy and orchestrate containerized services using Kubernetes and service mesh patterns, and own end-to-end feature delivery including infrastructure as code, monitoring, and operational runbooks.

Location: United States

Workplace: Onsite

Employment Type: Full time

Job Function: Government & Public Administration

Seniority: Mid level

Key Responsibilities

•Develop frameworks, automation, and tooling to improve efficiency and innovation for ML runtime developers.
•Implement and operate distributed systems and software components, including design, programming, testing, documentation, and bug fixing.
•Build developer-focused products and services to streamline interactions with the ML platform.
•Deploy and orchestrate containerized services in production using Kubernetes, service mesh, and ArgoCD, including related operational practices.
•Collaborate with Tech Leads and ML Engineers to elaborate requirements and drive end-to-end feature delivery, including infrastructure as code and adoption of new ML tools with reliability and scale in mind.

Pay and Benefits

Salary: USD 137,000 - 205,400 annually

Key Requirements

•US Citizenship is required.
•3 or more years of DevOps experience, including infrastructure automation and building CI/CD pipelines.
•Proficient in Python programming and able to design systems and write comprehensive technical design documents.
•Experience deploying and scaling machine learning runtime environments using DevOps pipelines for deployment, monitoring, and scaling.
•Experience with Kubernetes/Docker and CI/CD tooling such as Terraform, Git, Jenkins, and ArgoCD (plus related deployment/orchestration tools).

Experience:3+ yearsDevOpsMachine learningEnterprise SaaSDistributed systems

Education:Bachelor's

Skills:CollaborationProblem-solvingDocumentationProactivityInquisitiveness

Tech Stack:PythonKubernetesDockerAWSGCPTerraformGitJenkinsArgoCDService MeshCI/CDInfrastructure as codeRESTful servicesMicroservicesGrafana

Eligibility

Nationality:US National

Security Clearance:TS/SCI w/CI Poly

Company Brief

Workday

Provides cloud-based enterprise applications for human capital management, financial management, payroll, and analytics. Delivers unified HR and finance software suites to large organizations, enabling workforce planning, talent management, payroll, and financial reporting.

Industry: HR Tech

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Pleasanton, United States

Founded: 2005

Website LinkedIn

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Workday

1 week ago

Software Development Engineer - ML Ops (US Federal)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 27 minutes agoStatus: Live

Job Summary

Location: United States

Workplace: Onsite

Employment Type: Full time

Job Function: Government & Public Administration

Seniority: Mid level

Key Responsibilities

•Develop frameworks, automation, and tooling to improve efficiency and innovation for ML runtime developers.
•Implement and operate distributed systems and software components, including design, programming, testing, documentation, and bug fixing.
•Build developer-focused products and services to streamline interactions with the ML platform.
•Deploy and orchestrate containerized services in production using Kubernetes, service mesh, and ArgoCD, including related operational practices.
•Collaborate with Tech Leads and ML Engineers to elaborate requirements and drive end-to-end feature delivery, including infrastructure as code and adoption of new ML tools with reliability and scale in mind.

Pay and Benefits

Salary: USD 137,000 - 205,400 annually

Key Requirements

•US Citizenship is required.
•3 or more years of DevOps experience, including infrastructure automation and building CI/CD pipelines.
•Proficient in Python programming and able to design systems and write comprehensive technical design documents.
•Experience deploying and scaling machine learning runtime environments using DevOps pipelines for deployment, monitoring, and scaling.
•Experience with Kubernetes/Docker and CI/CD tooling such as Terraform, Git, Jenkins, and ArgoCD (plus related deployment/orchestration tools).

Experience:3+ yearsDevOpsMachine learningEnterprise SaaSDistributed systems

Education:Bachelor's

Skills:CollaborationProblem-solvingDocumentationProactivityInquisitiveness

Tech Stack:PythonKubernetesDockerAWSGCPTerraformGitJenkinsArgoCDService MeshCI/CDInfrastructure as codeRESTful servicesMicroservicesGrafana

Eligibility

Nationality:US National

Security Clearance:TS/SCI w/CI Poly

Company Brief

Workday

Industry: HR Tech

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Pleasanton, United States

Founded: 2005

Website LinkedIn