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.

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About the Team

Workday is the cloud-based SaaS company providing industry-leading software for HR, financials, workforce planning and employee learning to more than 40% of the Fortune 500. We are the Machine Learning Product team at Workday. Our focus is on the application of machine learning and statistical analysis to Workday’s products to serve our end users. We use diverse datasets to build data-driven products, which help the world’s largest organizations uncover insights and make strategic decisions about their people, finances, and business. We routinely work on data with high velocity, volume and variety, and we employ a modern machine learning distributed computing and big data software stack to deal with these challenges.
At Workday, we truly care about our people, that’s why we rank as the top 5 best places to work. To learn more about Workday ML, check out this video:
https://bit.ly/34efgyg

About the Role

This is an opportunity to be part of a growth team focused on MLOps. 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.

As a Senior Software 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 MLOps, CloudOps, 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 Python, Terraform and Kubernetes at scale.

You will use Workday’s vast computing resources on rich, exclusive datasets to deliver value that transforms the way our end-users experience WD. We will challenge you to apply your best creative thinking, analysis, problem-solving, and technical abilities to make an impact on thousands of enterprises and millions of people.

In this role, you would:

Work with multi-functional teams to deliver scalable, secure and reliable solutionsBuilding MLOps platform primarily using Kubeflow, and other ML ecosystem framework and services for building a unified ML Development experienceEffectively engage with data scientists, ML engineers, PMs and architects in requirements elaboration and drive technical solutionsOwn and develop cloud-based services from end to end including infrastructure as codeDesign and build software solutions for efficient organization, storage and retrieval of data to enable substantial scaleUnderstanding cloud computing and security to build robust cloud infrastructure and solutions for ML teamsBuild systems and dashboards to monitor service & ML healthLead in architecture reviews, code reviews and technology evaluationResearch, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind

About You

Basic Qualifications

6 or more years as a Software Development Engineer in ML domainBachelor’s and/or Master’s degree in Computer Science or Computer Engineering4 year’s experience designing, implementing, and maintaining robust MLOps services for deploying, monitoring, and scaling machine learning development primarily using Kubeflow or similar platformsProfessional experience in building web applications and microservices and API designSolid understanding on how to implement and manage CI/CD workflows to automate testing, integration, and delivery of machine learning componentsExperience in supporting large Kubernetes networks in production6 or more years of cloud programming experience preferably in Python or GoExperience with running and maintaining ML platforms such as: Databricks, Sagemaker, and or VertexAI

Other Qualifications

Implementation and operation of distributed systemsStay abreast of industry trends and emerging technologies, providing recommendations for continuous improvement of our DevOps and machine learning practicesTroubleshoot and resolve performance bottlenecks, system outages, and other operational issues in collaboration with the ML engineering teamsEnsure the security and compliance of machine learning platforms, implementing best practices for encryption, data protection and access controlsOptimize public cloud-based infrastructure (AWS, GCP) to support the computational requirements of machine learning workloadsExperience in managing relevant tools like Databricks and Sagemaker to perform efficient computation and management of large-scale data lakesExperience of data and/or ML systems with ability to think across layers of the stackDevelop and maintain monitoring and alerting systems for proactively identifying and addressing issues within the machine learning infrastructureExperience in leading or mentoring other team members

Workday Pay Transparency Statement

The annualized base salary ranges for the primary location and any additional locations are listed below.  Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits in Canada, please click here. For more information regarding Workday’s comprehensive benefits in the US, please click here.

Primary Location: CAN.ON.Toronto

Primary CAN Base Pay Range: $132,800 - $199,200 CAD

Additional US Location(s) Base Pay Range: $145,900 USD - $259,200 USD

Our Approach to Flexible Work
 

With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.

Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!