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Workday

Builds software to manage HR and finances

Software Development Engineer - ML Ops

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeReston, VA, USA

About the Job

Requirements

  • United States citizenship is required.
  • At least 3 years of DevOps experience, including infrastructure automation and building continuous integration/continuous delivery (CI/CD) pipelines.
  • Ability to perform system design and write comprehensive technical design documents.
  • Proficiency in Python programming.
  • Experience using Kubernetes and Docker to help developers scale efforts in creating products.
  • Experience with communication protocols, RESTful services, service-oriented architecture, distributed systems, and microservices.
  • Experience building comprehensive monitoring services.
  • Prior experience with enterprise software-as-a-service (SaaS) products.
  • Experience with monitoring tools such as Grafana.
  • Availability for rotating on-call support.
  • Proficiency with infrastructure automation tools such as Terraform, Git and Jenkins for CI/CD pipelines, and ArgoCD for continuous deployment.
  • A BS or MS in Computer Science or a related technical field.
  • Experience leading or mentoring team members and collaborating with a team, including understanding group dynamics, communication strategies, conflict resolution, and fostering an inclusive team.
  • Ability to obtain and maintain a U.S. government-issued security clearance; the role may require TS/SCI with CI Poly clearance.

Responsibilities

  • Develop frameworks, automation, and tooling that improve efficiency and innovation.
  • Apply Kubernetes, Docker, and Python to improve developer scalability for machine learning runtime inference applications.
  • Conceive, specify, design, program, document, test, debug, implement, and operate distributed systems and software, including applications, frameworks, and other software components.
  • Develop products and services that help developers interact efficiently with the machine learning platform.
  • Work with public cloud infrastructure, including Infrastructure as a Service, Amazon Web Services, and Google Cloud Platform, and apply capacity management principles.
  • Deploy and orchestrate containers in production environments using containers, Kubernetes, service mesh, ArgoCD, and related tools.
  • Engage with technical leads and machine learning engineers across teams to refine requirements and drive technical solutions.
  • Own and develop features end to end, including infrastructure as code.
  • Research, evaluate, prototype, and drive adoption of machine learning tools with reliability and scale in mind.
  • Proactively address and resolve issues, automate processes, and enable engineers to self-serve operational needs.
  • Provide rotating on-call support.
  • Design, implement, and maintain DevOps pipelines for deploying, monitoring, and scaling the machine learning runtime environment.
  • Collaborate with other machine learning teams to improve the product and engineering-process efficiency.
  • Create and maintain documentation and runbooks.

Desired Qualifications

  • Machine learning background.
  • Active TS/SCI with CI Poly clearance is preferred.

About the Company

Workday

Builds software to manage HR and finances

Workday builds cloud software that organizations use to manage employees, finances, and business plans. Its Human Capital Management and Financial Management applications handle processes such as hiring, payroll, expenses, accounting, and reporting, while Adaptive Planning helps teams build budgets and forecasts. Users work in connected applications with shared data and permissions, and Workday also sells AI tools that search information and carry out HR and finance tasks. Customers pay for subscriptions, with additional revenue from implementation, training, and other professional services. Workday was founded in 2005 and is headquartered in Pleasanton, California.

Company size
10,001+
Company stage
IPO
Headquarters
Pleasanton, CA
Founded
2005

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