Machine Learning Engineer III

Workday•Boulder, CO

1d•$136,200 - $240,000•Hybrid

About The Position

Workday is seeking a Machine Learning Engineer III to join their Agent Factory team. This role involves designing and building core ML systems for AI agents, working within a small, senior, cross-functional pod. The engineer will own the integration of models, agent logic, and orchestration layers in production, covering the full lifecycle from problem framing and data strategy to deployment, monitoring, and continuous improvement. The position focuses on implementing and evolving frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops, ensuring scalability, observability, and enterprise readiness. This role is at the intersection of ML and platform engineering, requiring close collaboration with software engineers, product managers, and data scientists to deeply integrate agents into the Workday stack. The engineer will stay current with emerging techniques in agentic architectures and apply strong engineering judgment to create reliable, explainable systems operating at global scale.

Requirements

5+ yrs experience as part of a data science, machine learning software development team or relevant work in a PhD or equivalent experience program.
3+ years experience using Python and frameworks such as Pytorch, TensorFlow
2+ years of experience related to machine learning, deep learning, NLP, GenAI, multi-agent AI systems, distributed training, model hosting, etc
B.S. or M.S. in relevant fields (Computer Science, Mathematics, Engineering).
Experienced in handling large-scale, complex data sets, data modeling, and productizing machine learning algorithms.
Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders.

Nice To Haves

PhD or equivalent experience preferred
Strong experience building applied machine learning products, including taking a product through design, implementation, and to production is a plus.
Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams.

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 across the full lifecycle from problem framing and data strategy to deployment, monitoring, and continuous improvement.
Implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops.
Ensure 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 while applying strong engineering judgment to turn them into systems that are reliable, explainable, and built to operate at global scale.
Own data exploration and transformation, feature & prompt engineering, design and enhance ML models/frameworks.
Take ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement.