Sr. Machine Learning Engineer

Workday is hiring a Senior Machine Learning Engineer to lead technical direction on the AI Model Serving platform supporting production Workday agents and ML workloads at scale.

Responsibilities

• Provide technical leadership by making 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 teams on new components and enhancements
• Evaluate and adopt new technologies made available within Workday and across the broader industry
• Troubleshoot, improve, and scale continuous integration software pipelines
• Build relationships with software engineers, machine learning engineers, and data scientists on partner teams
• Respond to alerts and debug production issues to maintain platform health and reliability
• Review pull requests and enforce consistency, performance, readability, and security
• Develop documentation to share engineering knowledge

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 using hardware metrics
• Deep experience designing, building, and scaling production-grade distributed systems
• Understands 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 systems built with Python-based frameworks
• Understands how large language models and traditional ML models are served, scaled, and monitored in production
• Can design abstractions that support both traditional ML and LLMs effectively
• Can design and maintain monitoring strategies for system health, performance, and cost visibility
• Excellent written and verbal communication skills, including producing clear design documents and articulating complex technical ideas
• Collaborative approach to engineering, 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
• Owns the services that support all production AI workloads
• Acts as a gateway to vendor-hosted LLMs including GCP, AWS Bedrock, and Gemini
• Hosts and scales Workday’s internal models
• Hosts thousands of traditional ML models across sharded Ray Serve clusters and maintains Workday’s production model registry
• Handles approximately 2,000 requests per second, with peaks above 10,000 RPS in largest clusters
• Supports scaling architecture for bringing 20+ new AI agents into production
• Provides infrastructure to host and tune open-weight LLMs within Workday’s stack
• Focuses on performance and reliability, including reducing core latency while maintaining stability
• Implements enterprise governance, including unified vendor interface hardening and advanced cost-governance controls

About the Role

• Serve as a technical leader shaping the platform vision and direction
• Drive outcomes by participating in critical design decisions
• Help set a positive and inclusive team culture
• Directly influence Workday’s ability to serve AI at scale, spanning traditional ML models through large language models for Workday agents

Workday Pay Transparency Statement

• Primary Location: USA.CO.Boulder
• Primary Location Base Pay Range: $171,600 USD - $257,400 USD
• Additional US Location(s) Base Pay Range: $163,000 USD - $288,000 USD
• Role may be eligible for Workday Bonus Plan or role-specific commission/bonus, plus annual refresh stock grants

Flexible Work

• With Flex Work, spend at least 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.

Fair Chance Law

Workday will consider for employment qualified applicants with arrest and conviction records pursuant to applicable Fair Chance law.

Equal Opportunity

Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.

Reasonable Accommodations and AI Tools for Employment Decision-Making

• Workday is committed to providing reasonable accommodations for qualified individuals during the application process
• Workday is committed to accommodations regarding the use of AI tools for employment decision-making

Accommodations Contact

If you require a reasonable accommodation, email [email protected], as far in advance as possible.

Workday Careers and Recruiting Fee

• 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 or coaching services to apply for a job