Sr. Machine Learning Engineer

Workday is hiring a Senior Machine Learning Engineer for the AI Model Serving team, responsible for technical leadership on a production platform that powers Workday agents and large-scale machine learning workloads. The role focuses on designing and operating high-throughput systems, improving reliability and performance, and supporting governance and cost controls for AI model serving.

Key Responsibilities

• Provide technical leadership by making critical design decisions that improve platform performance, reliability, and scalability.
• Design, implement, and maintain large-scale systems that move machine learning models into production.
• Author design documents to align teams on new system components and enhancements to existing components.
• Evaluate and adopt new technologies available within Workday and across the broader industry.
• Troubleshoot, improve, and scale continuous integration software pipelines.
• Collaborate with software engineers, machine learning engineers, and data scientists across partner teams.
• Respond to alerts and debug production issues to maintain platform health and reliability.
• Review pull requests with focus on consistency, performance, readability, and security.
• Develop documentation to share knowledge across the engineering organization.

Required Qualifications

• 6+ years of related experience in software development, with emphasis on building and operating large-scale distributed systems.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience).
• Deep hands-on experience deploying and scaling workloads on Kubernetes, with a focus on GPU resource management.
• Understanding of optimizing GPU utilization for hosting and tuning smaller open-weight LLMs using modern inference engines (for example, vLLM and SGLang).
• Familiarity with GPU memory constraints, serving tuned models such as LoRA, and autoscaling based on hardware metrics.
• Deep experience designing, building, and scaling production-grade distributed systems.
• Working knowledge of the full software development lifecycle, including coding standards, testing, code reviews, source control, and deployment for complex, high-throughput platforms.
• Strong proficiency in Python, including production-level code and building systems using Python-based frameworks.
• Familiarity with both large language models and traditional ML models, including serving, scaling, and production monitoring.
• Ability to understand operational differences across model types and design abstractions that support both effectively.
• Experience designing and maintaining monitoring strategies that provide visibility into system health, performance, and cost.
• Excellent written and verbal communication skills, including producing clear design documents and articulating complex technical ideas to build consensus.
• Collaborative mindset, including experience mentoring engineers and fostering an inclusive team environment.

Technologies

• Ray Serve
• Kubernetes
• GPU
• vLLM
• SGLang
• LoRA
• Python
• Continuous integration

About the Team

• The AI Model Serving team is the engine behind every production Workday agent and machine learning use case.
• Owns services that power all production AI workloads.
• Acts as the gateway to vendor-hosted LLMs including GCP, AWS Bedrock, and Gemini, while also serving and scaling Workday-hosted internal models.
• Hosts thousands of traditional ML models across sharded Ray Serve clusters and maintains Workday’s production model registry.
• Supports approximately 2,000 requests per second, with peaks above 10,000 RPS in the largest clusters.
• Scaling architecture supports upgrading systems to support 20+ new AI agents as they enter production.
• Open-weight LLM hosting includes infrastructure for hosting and tuning open-source LLMs within Workday’s stack.
• Focuses on performance and reliability by driving down core latency while maintaining stability.
• Implements enterprise governance by hardening a unified vendor interface and adding advanced cost-governance controls.

About the Role

As a Senior Machine Learning Engineer on the AI Model Serving team, you will shape the platform’s vision and direction while driving outcomes through critical design decisions. Your work will influence Workday’s ability to serve AI at scale, covering traditional ML models through to the latest large language models that power Workday’s agents.

Location and Compensation

• Location: Boulder, CO (hybrid)
• Salary Range: USD 163,000 - 257,400 per year
• Workday Pay Transparency Statement (Primary Location): USA.CO.Boulder, base pay range $171,600 - $257,400
• Additional US Locations (Base Pay Range): $163,000 - $288,000
• Total Compensation Note: May be eligible for a Workday Bonus Plan or role-specific commission/bonus and annual refresh stock grants

Flexible Work

With Flex Work, spend at least half (50%) of your time each quarter in the office or in the field with customers, prospects, and partners (depending on role).

Application Deadline

The application deadline for this role is the same as the posting end date: 10/30/2026.

Equal Opportunity and Accommodations

• Workday considers qualified applicants with arrest and conviction records pursuant to applicable Fair Chance law.
• Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
• Reasonable accommodations are available during the application process.
• If you need a reasonable accommodation, email [email protected] as far in advance as possible.

Workday Careers Policy

• Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.
• Workday will never ask candidates to pay a recruiting fee or pay for consulting or coaching services to apply for a job.