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: 28 minutes agoStatus: Live

Job Summary

Design and deliver highly scalable features for a Machine Learning Runtime platform supporting U.S. federal agencies. Build and operate distributed systems, developer frameworks, and automation tooling using Python, Kubernetes, and Docker. Own end-to-end features including infrastructure as code, deploy and orchestrate containers in production, and collaborate with ML and software teams to improve reliability, monitoring, and developer self-service operational needs. Provide rotational on-call support and help evaluate new ML tools.

Location: United States

Workplace: Hybrid

Employment Type: Full time

Job Function: Government & Public Administration

Seniority: Mid level

Key Responsibilities

•Develop frameworks, automation, and tooling to improve efficiency and innovation.
•Apply technologies like Kubernetes, Docker, and Python to enhance scalability for ML runtime inference applications.
•Implement and operate distributed systems across the software lifecycle, including designing, testing, debugging, and maintaining components.
•Develop products and services that streamline developers’ interactions with the ML platform.
•Work with public clouds (IAAS, AWS, GCP) using capacity management principles; deploy and orchestrate containers in production; support rotational on-call.

Pay and Benefits

Salary: USD 137,000 - 205,400 annually

Key Requirements

•US citizenship is required.
•3+ years of DevOps experience, including infrastructure automation and building CI/CD pipelines.
•Proficient in Python programming.
•Good in system design and writing comprehensive technical design documentation.
•Experience using Kubernetes and Docker to help deploy, monitor, and scale machine learning runtime environments.

Experience:Enterprise SaaSMachine learningDevOpsCloud

Skills:CollaborationProblem-solvingTechnical documentationProactive issue resolutionAutomation mindset

Tech Stack:PythonKubernetesDockerAWSGCPIAASCI/CDTerraformGitJenkinsArgoCDService MeshRESTful servicesMicroservicesInfrastructure as code

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: 28 minutes agoStatus: Live

Job Summary

Location: United States

Workplace: Hybrid

Employment Type: Full time

Job Function: Government & Public Administration

Seniority: Mid level

Key Responsibilities

•Develop frameworks, automation, and tooling to improve efficiency and innovation.
•Apply technologies like Kubernetes, Docker, and Python to enhance scalability for ML runtime inference applications.
•Implement and operate distributed systems across the software lifecycle, including designing, testing, debugging, and maintaining components.
•Develop products and services that streamline developers’ interactions with the ML platform.
•Work with public clouds (IAAS, AWS, GCP) using capacity management principles; deploy and orchestrate containers in production; support rotational on-call.

Pay and Benefits

Salary: USD 137,000 - 205,400 annually

Key Requirements

•US citizenship is required.
•3+ years of DevOps experience, including infrastructure automation and building CI/CD pipelines.
•Proficient in Python programming.
•Good in system design and writing comprehensive technical design documentation.
•Experience using Kubernetes and Docker to help deploy, monitor, and scale machine learning runtime environments.

Experience:Enterprise SaaSMachine learningDevOpsCloud

Skills:CollaborationProblem-solvingTechnical documentationProactive issue resolutionAutomation mindset

Tech Stack:PythonKubernetesDockerAWSGCPIAASCI/CDTerraformGitJenkinsArgoCDService MeshRESTful servicesMicroservicesInfrastructure as code

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