Sr. Machine Learning Engineer

Workday is hiring a Senior Machine Learning Engineer on the AI Model Serving team in a hybrid role based in Boulder, CO.

Responsibilities

• Provide technical leadership by driving critical design decisions that improve performance, reliability, and scalability across the platform
• Design, implement, and maintain large-scale systems that move ML models into production
• Create design documents to align stakeholders on new components and enhancements
• Evaluate and adopt new technologies introduced within Workday and across the industry
• Troubleshoot, improve, and scale continuous integration pipelines
• Collaborate across partner teams with software engineers, machine learning engineers, and data scientists
• Respond to alerts and debug production incidents to maintain platform health
• Review pull requests and enforce standards for consistency, performance, readability, and security
• Develop documentation to share knowledge with other engineers

Requirements

• 6+ years of related experience in software development, focused 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
• Knowledge of optimizing GPU utilization for hosting and tuning smaller open-weight LLMs using inference engines such as vLLM and SGLang
• Familiarity with GPU memory constraints, serving tuned models such as LoRA, and autoscaling hardware metrics
• Deep experience designing, building, and scaling production-grade distributed systems
• Understanding of the full software development lifecycle, including coding standards, testing, code reviews, source control, and deployment for complex, high-throughput platforms
• Deep proficiency in Python, including production-level code and Python-based framework systems
• Familiarity with both large language models and traditional ML models, including serving, scaling, and production monitoring
• Ability to understand operational differences and design abstractions that support both model types effectively
• Ability to design and maintain monitoring strategies that provide insight into health, performance, and cost
• Excellent written and verbal communication skills, including writing design documents and articulating complex technical ideas to build consensus
• Collaborative engineering approach, including mentoring 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 powers every production Workday agent and machine learning use case
• Own the services that enable production AI workloads
• Act as a gateway to vendor-hosted LLMs (GCP, AWS Bedrock, Gemini) and the primary platform for Workday-hosted internal models
• Host thousands of traditional ML models across sharded Ray Serve clusters and maintain the production model registry
• Platform scale includes ~2,000 requests per second, peaking at over 10,000 RPS in largest clusters
• Scaling architecture supports upgrades to support 20+ new AI agents going into production
• Open-weight LLM hosting includes designing infrastructure to host and tune open-source LLMs within the stack
• Performance and reliability focus on reducing core latency while maintaining stability
• Enterprise governance includes hardening a unified vendor interface and implementing cost-governance controls

Role Focus

• Provide technical leadership that shapes the platform vision and direction
• Make central design decisions and drive team outcomes
• Help set a positive and inclusive engineering culture
• Impact Workday’s ability to serve AI at scale, spanning traditional ML models through the latest large language models for Workday agents

Compensation

• Salary (USD): $163,000 - $257,400 per year
• Primary Location: USA.CO.Boulder
• Primary Location Base Pay Range: $171,600 - $257,400
• Additional US Location(s) Base Pay Range: $163,000 - $288,000
• Total compensation may include eligibility for the Workday Bonus Plan or role-specific commission/bonus, plus annual refresh stock grants

Location and Work Model

• Location: Boulder, CO (hybrid)
• 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 Details

• Application deadline: 10/30/2026

Equal Opportunity and Legal Notices

• Workday will consider 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

Accommodations and AI Use

• Workday provides reasonable accommodations for qualified individuals during the application process
• Workday supports use of AI tools for employment decision-making with appropriate commitments
• Accommodations contact: [email protected]

Recruiting Fee Statement

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