Workday

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.. Design, implement, and maintain robust DevOps pipelines for deploying, monitoring, and scaling machine learning development and data engineering. Experience in managing relevant tools like Databricks and Sagemaker to perform efficient computation and management of large scale data lakes. Experience with Databricks, Sagemaker, & Apache-Spark

principal devops 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. 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. 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. About The Role In this role, you would: <ul><li>Work with multi-functional teams to deliver scalable, secure and reliable solutions </li><li>Effectively engage with data scientists, ML engineers, PMs and architects in requirements elaboration and drive technical solutions </li><li>Own and develop features from end to end including infrastructure as code </li><li>Design and build solutions for efficient organization, storage and retrieval of data to enable substantial scale </li><li>Build systems and dashboards to monitor service & ML health. </li><li>Lead in architecture reviews, code reviews and technology evaluation </li><li>Research, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind </li> </ul>About You Basic Qualifications <ul><li>6 or more years of validated industry experience </li><li>Bachelor’s and/or Master’s degree, preferably in CS, or equivalent experience </li><li>Design, implement, and maintain robust DevOps pipelines for deploying, monitoring, and scaling machine learning development and data engineering </li><li>Stay abreast of industry trends and emerging technologies, providing recommendations for continuous improvement of our DevOps and machine learning practices </li><li>Troubleshoot and resolve performance bottlenecks, system outages, and other operational issues in collaboration with the ML engineering teams </li><li>Optimize public cloud-based infrastructure (AWS, Azure, or GCP) to support the computational requirements of machine learning workloads </li><li>Implement and manage CI/CD workflows to automate testing, integration, and delivery of machine learning components </li><li>Develop and maintain monitoring and alerting systems for proactively identifying and addressing issues within the machine learning infrastructure </li><li>Ensure the security and compliance of machine learning platforms, implementing best practices for encryption, data protection and access controls </li><li>Experience in managing relevant tools like Databricks and Sagemaker to perform efficient computation and management of large scale data lakes </li><li>Experience in supporting your work in production </li><li>6 or more years of DevOps or programming experience preferably in Python, Java or Scala </li> </ul>Other Qualifications <ul><li>Implementation and operation of distributed systems </li><li>Experience of data and/or ML systems with ability to think across layers of the stack </li><li>Experience with Databricks, Sagemaker, & Apache-Spark </li><li>Experience in leading or mentoring other team members </li> </ul>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, please click here. Primary Location: USA.GA.Atlanta Primary Location Base Pay Range: $124,700 USD - $187,100 USD Additional CAN Location(s) Base Pay Range: $107,600 - $161,400 CAD 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 simplyspend 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! #J-18808-Ljbffr

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