About the role

Principal Machine Learning Engineer designing the core ML systems for AI agents at Workday. Collaborating in cross-functional teams to integrate ML solutions into the platform.

Responsibilities

Design and build the core ML systems behind Workday’s next generation of AI agents
Own how models, agent logic, and orchestration layers come together in production
Implement and evolve frameworks for LLM-powered agents, ensuring solutions are scalable, observable, and enterprise-ready
Partner closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack
Stay hands-on with emerging techniques in agentic architectures

10+ years experience as a member of a data science or machine learning engineering team building applied machine learning products at scale
4+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow
6+ years of professional experience in building services to host machine learning models in production at scale
3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP)
Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams
Bachelor's (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent