MLOps Engineer

Your work days are brighter here.

At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.

About the Team

This is an opportunity to be part of a growth team focused on ML DevOps and ML Ops. We build ML capabilities into our products, and you would be building part of the next generation of Workday technology. We believe predictive products can be as ground-breaking to the next generation of technology as mobile was to the last.

About the Role

In this role, you would:

• Work with multi-functional teams to deliver scalable, secure and reliable solutions

• Effectively engage with data scientists, ML engineers, PMs and architects in requirements elaboration and drive technical solutions

• Own and develop features from end to end including infrastructure as code. 

• Design and build solutions for efficient organization, storage and retrieval of data to enable substantial scale

• Build systems and dashboards to monitor service & ML health.

• Lead in architecture reviews, code reviews and technology evaluation.

• Research, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind.

About You

As a DevOps engineer you will help develop ML powered features and experiences for every user across our HR & Talent product portfolio. You will work closely with ML engineers and other software teams to deliver critically important infrastructure and software frameworks that enable machine learning across Workday’s product ecosystem. You will apply modern ML Ops, Devops, and data engineering stacks to enable development,  training, deployment, and lifecycle management of a variety of ML capabilities; supervised and unsupervised, deep learning and classical. You will be responsible for the design & development of new APIs/microservices and deploy them using Terraform/Kubernetes at scale.

Basic Qualifications

• You have a BS/MS in Computer Science or a related technical field

• Building frameworks, automation, and tooling to enable a culture of quality within the organization.

• Leveraging technologies like kubernetes/docker to help our developers scale their efforts in creating new and innovative products.

• Creating products and services that enable developers to programmatize their interactions with the ML platform

• Experience working with private and public clouds (IAAS, GCP, AWS, etc) and capacity management principles.

• Experience deploying to and orchestrating containers in production environments (Containers, Kubernetes, Service Mesh and related technologies).

• Experience with communication protocols, restful services, service-oriented architecture, distributed systems, and micro-services.

• Experience with Infrastructure automation (Terraform, Ansible, etc.), CI/CD pipelines (GIT, Jenkins etc), and configuration management tools( Ansible, Chef etc).

• Experience with building a suite of monitoring services. 

• Strong mission to put pro-active solutions in place to prevent future problems and automate processes/build services such engineers can self-service their operational requirements and enhance productivity.

• Experience creating and maintaining documentation and troubleshooting runbook.

• Available for on-call support on a rotating basis. 

Bonus Points:

• Machine learning background 

• Prior experience with enterprise SaaS products

• Expertise in secure network design and implementation

• Program management experience and familiar with Agile/Scrum /JIRA.

Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additi