Sr. Machine Learning Engineer

Your work days are brighter here. 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. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.

The AI Model Serving team is the engine behind every production Workday agent and machine learning use case. We own the services that power all production AI workloads, acting as both the gateway to vendor-hosted LLMs (GCP, AWS Bedrock, Gemini) and the primary platform where Workday hosts and scales its internal models. We operate at scale, hosting thousands of traditional ML models across sharded Ray Serve clusters and maintaining Workday's production model registry.

In the year ahead, our engineering roadmap is highly ambitious. We are focused on:
Scaling Architecture:
Upgrading our systems to seamlessly support 20+ new AI agents going into production. Hosting Open-Weight LLMs:
Designing the infrastructure to host and tune open-source LLMs directly within our stack. Performance & Reliability:
Architecting optimizations to drive down core latency while maintaining the rock-solid stability our high-throughput production systems demand. Enterprise Governance:
Hardening our unified vendor interface and implementing advanced cost-governance controls.

Our culture is built on focus, camaraderie, and high performance. We are a friendly, dedicated group that takes pride in building and operating one of the most heavily used services at Workday.

If you are energized by working on the infrastructure that sits at the very heart of Workday's AI strategy, this is the team for you.

As a Senior Machine Learning Engineer on the AI Model Serving team, you will be a technical leader who helps shape the vision and direction of the platform. You will play a central role in making critical design decisions, driving outcomes across the team, and setting a positive and inclusive team culture. Your work will directly impact Workday's ability to serve AI at scale — from traditional ML models to the latest large language models powering Workday's agents.

• Lead the team technically by making critical design decisions that drive performance, reliability, and scalability across the platform.
• Design, implement, and maintain large-scale systems that enable moving ML models to production.
• Write design documents to build consensus for new system components and enhancements to existing components.
• Evaluate and uptake new technologies made available within Workday and across the broader industry.
• Troubleshoot, improve, and scale continuous integration software pipelines.
• Develop relationships with software engineers, machine learning engineers, and data scientists on partner teams.
• Respond to alerts and debug production issues to…