Intermediate or Senior MLOps Engineer - US Federal

Workday-posted 7 months ago
$128,800 - $193,200/Yr
Full-time • Mid Level
Hybrid • Beaverton, OR
Publishing Industries
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At Workday, we are looking for a Software Engineer to join our growth team focused on MLOps. This role involves building machine learning capabilities into our products, specifically within our HR & Talent product portfolio. You will work closely with ML engineers and other software teams to develop ML-powered features and experiences, utilizing modern MLOps, CloudOps, and data engineering stacks. Your responsibilities will include designing and developing new APIs/microservices, deploying them using Python, Terraform, and Kubernetes, and leveraging Workday's vast computing resources to deliver transformative value to our end-users.

  • Work with multi-functional teams to deliver scalable, secure, and reliable solutions.
  • Build MLOps platform primarily using Kubeflow and other ML ecosystem tools for a unified ML Development experience.
  • Communicate effectively with data scientists, ML engineers, PMs, and architects to elaborate requirements and drive technical solutions.
  • Own and develop cloud-based services from end to end, including infrastructure as code.
  • Design and build software solutions for efficient organization, storage, and retrieval of data.
  • Understand cloud computing and security to build robust cloud infrastructure for ML teams.
  • Build systems and dashboards to monitor service and ML health.
  • Lead architecture reviews, code reviews, and technology evaluations.
  • Research, evaluate, prototype, and drive adoption of new ML tools.
  • 5 or more years of proven industry experience.
  • Bachelor's and/or Master's degree in Computer Science or Computer Engineering.
  • Experience in designing, implementing, and maintaining robust MLOps services primarily with Kubeflow.
  • Proficiency in troubleshooting and resolving performance bottlenecks and system outages.
  • Experience optimizing public cloud-based infrastructure (AWS, GCP) for machine learning workloads.
  • Experience implementing and managing CI/CD workflows for machine learning components.
  • Professional experience in building web applications, microservices, and API design.
  • Experience supporting large Kubernetes networks in production.
  • 5 or more years of cloud programming experience, preferably in Python or Go.
  • Experience with running and maintaining Databricks, Sagemaker, and Apache Spark.
  • 8 or more years of validated industry experience for Senior Software Engineer role.
  • Experience in managing relevant tools like Databricks and Sagemaker for large scale data lakes.
  • Experience in leading or mentoring team members.
  • Ability to think across layers of the stack in data and/or ML systems.
  • Workday Bonus Plan eligibility.
  • Annual refresh stock grants.
  • Flexible work schedule with a combination of in-person and remote work.
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