Machine Learning Engineer III / Senior Machine LearningEngineer - AI Platform

We’re obsessed with making hard work pay off, for our

people, our customers, and the world around us. As a Fortune 500

company and a leading AI platform for managing people, money, and

agents, we’re shaping the future of work so teams can reach their

potential and focus on what matters most. The minute you join,

you’ll feel it. Not just in the products we build, but in how we

show up for each other. Our culture is rooted in integrity,

empathy, and shared enthusiasm. We’re in this together, tackling

big challenges with bold ideas and genuine care. We look for

curious minds and courageous collaborators who bring sun‑drenched

optimism and drive. Whether you’re building smarter solutions,

supporting customers, or creating a space where everyone belongs,

you’ll do meaningful work with Workmates who’ve got your back. In

return, we’ll give you the trust to take risks, the tools to grow,

the skills to develop, and the support of a company invested in you

for the long haul.

About The Team This is a

very exciting opening in the AI Platform team in our Agent

Optimization & Evaluation, and Information Retrieval team. We

are the Optimization and "Ground Truth" engine for Workday’s AI

transformation, building the critical infrastructure that empowers

over 65% of the Fortune 500.

Mission

Agent Optimization & Evaluation :

Providing the algorithms and rigorous data‑driven frameworks to

validate, scale, and optimize AI agents across our entire

enterprise suite.

Information Retrieval :

Developing the intelligence layer that bridges human language and

enterprise data through advanced semantic search and natural

language‑to‑code (SQL / Python) execution.

Join Us?

The Data & Frontier : Solve unique

challenges in Agentic AI using exclusive, high‑integrity enterprise

datasets.

Impact at Scale : Your work acts as

the optimizer and gatekeeper of quality for products reaching 31

million users globally.

People‑First Culture :

We balance high‑intensity innovation with a commitment to

sustainable work‑life integration.

About The

Role We are seeking pragmatic ML and Senior ML Engineers to drive

the applied research, deployment, and optimization of our Agentic

AI, Search, and Semantic Parsing products. In this role, you will

bridge the gap between deep research and production, embedding

cutting‑edge agents directly into the Workday ecosystem. Leveraging

our vast computing power and exclusive datasets, you will solve

complex technical challenges to deliver transformative value to

millions of users. If you are ready to apply creative

problem‑solving to global‑scale ML systems, we want to hear from

you.

Responsibilities

Architect

Agentic AI : Design and deploy sophisticated reasoning, planning,

and swarm agents that interact seamlessly with enterprise data and

support continuous, lifelong learning.

Drive

Meta‑ML & Optimization : Develop algorithms for automated

node‑level optimization within agent graphs, identifying the best

LLM and prompt configurations for every workflow step. Build

recommender systems for engineering teams to drive optimal

evaluation of their agents.

Advance

Information Retrieval : Build hybrid, agentic search systems and

semantic parsing products (Text-to‑SQL / Python) utilizing vector

search, reasoning, and fine‑tuning for structured

output.

Scale Evaluation & Observability :

Engineer cloud‑based pipelines (Kubeflow) and A / B testing

frameworks for rigorous offline / online evaluation, failure

attribution, and safety monitoring.

Lead the

ML Lifecycle : Own the end‑to‑end MLOps process—from exploration and

prompt engineering to scalable production deployment—ensuring

high‑quality, reliable performance.

Define

Strategic Roadmaps : Independently identify ML opportunities,

propose high‑impact solutions to leadership, and integrate industry

best practices across the

organization.

Collaborate with Autonomy : Work

cross‑functionally with PMs and Engineers to deliver "AI‑first"

products, enjoying full ownership of your work within a supportive,

growth‑oriented culture.

Basic Qualifications

MLE III)

Deep Technical ML Capability : 3+

years of experience researching, developing and deploying

production‑grade ML systems, including expertise in deep learning,

NLP, Information Retrieval, and recommender systems using

frameworks such as PyTorch or

TensorFlow.

Generative AI & Agentic

Systems : 0.5+ years of proven track record of building and

evaluating NLP and LLM‑powered products, including expertise in RAG

architectures, agentic frameworks (e.g., LangChain / LangGraph), and

long‑context LLM applications (e.g.,

Text-to-SQL).

Engineering Excellence : 0.5+

years expert‑level Python experience with a focus on modular

library design, asynchronous patterns, and scalable system

architecture (state management / error handling) for

non‑deterministic AI outputs.

Basic

Qualifications (Senior MLE)

Deep Technical ML

Leadership : 6+ years