Principal, Machine Learning 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

We're working on making machine learning core to Workday's products by building data products and auto-ml models 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

We're building ML powered Search and Generative AI services and platforms to modernize how users interact with workday - adding ease, intelligence and efficiency to everyday interactions. All of these capabilities are designed to be applied across a wide range of applications within Workday.

As a machine learning engineer, you will help develop tailored experiences for every user powered by advanced Large Language Models (LLMs), personalization, and predictive analysis. You will work closely with other ML engineers and software developers to deliver ML solutions that enable ML powered search and user experience across Workday’s product ecosystem. You will apply current 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’s 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 users. Sound like your kind of challenge?

About You

Key Responsibilities:

• Own exploration, design and execution of advanced ML models, algorithms and frameworks that deliver value to our users.

• Preprocess and clean large amounts of unstructured text data to ensure quality and consistency for Natural Language Processing (NLP) and other ML model training.

• Engineer relevant features from textual data to facilitate accurate model predictions and classification.

• Apply machine learning techniques including LLMs, deep learning including generative models, natural language understanding, sentiment analysis, topic modeling, and named entity recognition to analyze large sets of HR-related text data, and design and launch pioneering cloud based machine learning architectures.

• Train, validate, and fine-tune machine learning models using large-scale datasets to achieve robust performance.

• Own the performance, scalability, metric based deployed evaluation, and ongoing data driven enhancements of your products.

• Collaborate across teams to deliver your products through Workday end user applications.

• Be given autonomy and ownership over your work, but with the support of the entire organization.

• Keep abreast of the latest advancements in NLP research, techniques, and tools.

• Have extraordinary opportunities for career growth and learning in a fast-growing, forward-looking company.

Basic Qualifications:

• Bachelor’s (Master’s preferred) degree in engineering, computer science, physics, math or equivalent.

• 6 or more years of experience developing, deploying, and supporting high-performance systems in production

• 6 or more years of experi