Machine Learning Engineer, Workday

• Do you want to build AI-powered software that impacts millions of people every day?
• You are a strong technical leader with deep Python expertise and solid software engineering skills, capable of writing beautiful, well-designed code while delivering solutions efficiently
• Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent
• 3+ yrs experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation
• 3+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models
• 3+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)

Desirable

• The AI Core team, part of Workday’s AI Platform organization, tackles challenging problems at the intersection of machine learning, agentic reasoning, and enterprise-scale systems
• Our work delivers critical AI platform capabilities and differentiated, deep-value agent applications
• As a Machine Learning Engineer on the AI Core team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG
• You will collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem and use current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised
• Additionally, you will develop and deploy new APIs/services using Docker/Kubernetes at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers
• Own exploration, design and implementation of features for our sophisticated ML platforms, pipelines and services
• Be responsible for evaluation, scalability and observability of these features
• Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud-based machine learning architectures
• Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
• Serve as a technical role model for more junior engineers

• End Date: April 30, 2026