Job Description

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\xe2\x80\x99s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don\xe2\x80\x99t 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 We\'re working on making machine learning core to Workday\'s products by building data products and generalizable ML solutions that can be scaled out to hundreds of use cases within Workday. As part of a global, high-growth technology company, our work supports thousands of the largest global companies and more than 30 million end users. You will solve complex problems and influence machine learning and application development across Workday. Our team is passionate about teaching and learning, so be eager to share your expertise and learn from us. Join us as we change the way millions of people work.

About the Role

This is an opportunity to be part of a growth team focused on building ML capabilities into our products, and part of the next generation of Workday technology. We believe AI/ML products can be as transformative to the next generation of technology as mobile was to the last.

As a principal machine learning engineer, you will work closely with other ML engineers and software developers to deliver ML solutions that enable ML powered products throughout Workday\xe2\x80\x99s product ecosystem. You will utilize modern software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised, deep learning and classical. You will develop new APIs & microservices and deploy them using docker/kubernetes at scale.

You will use Workday\xe2\x80\x99s vast computing resources on rich, exclusive datasets to deliver value that transforms the way our customers make decisions and run their business. 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.

Sound like your kind of challenge?

Key Responsibilities:

Bring best-practices from within and outside the organization, and influence workflow and technology choices across the team.

Own the technologies that drive product success, with a strong understand of scalability, trade-offs and limitations

Define an architectural roadmap to continue to expand business impact of the team. Demonstrate consistency & reliability. Serve as a technical role model for more junior engineers.

Provide and receive PR feedback that helps you and your colleagues improve their practice and learn from each other.

Evaluate, decide on, and lead implementation of new technologies and ML services within Workday.

Contribute to design documents for new systems components and enhancements to existing components

Develop relationships with software engineers, DevOps engineers, and product managers across our organization

Respond to alerts and debug production issues as part of on-call rotation

About You

Basic Qualifications

5 or more years experience as part of a data science, machine learning, or other software development team

Proven ability to use statistical analysis and machine learning algorithms, especially for supervised and unsupervised methods to solve business/customer problems.

4 or more years of advanced proficiency in Python and supporting numeric libraries

Experience in machine learning frameworks & toolkits such as Tensorflow, Pytorch, Sklearn

Experience building applied machine learning products, including taking a product through design, implementation, and to production.

Experience in delivering products with large-scale, complex data sets, data modeling, and productizing machine learning algorithms.

B.S. in a relevant field - (E.g. Computer Science, Mathematics, Engineering). M.S. or Ph.D are nice, but not required.

Other Qualifications

Advanced understanding of a variety of modeling techniques including classical and deep learning

Ability to teach, mentor and lead through influence

Resilience to obstacles, and ability to solve problems by collaborating with teams across the organization

Workday Pay Transparency Statement - United States

The annualized base salary ranges for the primary location and any additional locations in the United States (US) 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\xe2\x80\x99s 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\xe2\x80\x99s comprehensive benefits, please .
Additional US Location(s) Base Pay Range: $168,700 - $306,400

Our Approach to Flexible Work

With Flex Work, we\xe2\x80\x99re 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!

Workday