Machine Learning Engineer / Senior Machine Learning Engineer (AI Platform)

Role overview

Join Workday’s AI Platform organization as a Machine Learning Engineer / Senior Machine Learning Engineer (AI Platform). You will build core platform capabilities that enable AI agents—including execution, orchestration, state management, and reliability—so new AI use cases can be productionized for users at massive scale.

Responsibilities

• Design and build core platform capabilities to develop, host, and operate AI agents at scale
• Develop infrastructure and services for agent execution, orchestration, state management, and runtime reliability
• Partner with cross-functional teams to productionize new agent use cases
• Establish common platform patterns and best practices across engineering and AI teams

Requirements

• 3+ years designing scalable, reliable systems with focus on scalability, reliability, observability, and maintainability
• 3+ years experience in a data science/ML software development team (or PhD / equivalent program)
• 6+ years software engineering experience, including production-grade backend/ML/platform systems
• 8+ years experience with Python building reliable, maintainable production services
• 3+ years with distributed systems, APIs, asynchronous workflows, and service-oriented architecture
• Strong ability to drive projects from concept to production in an ambiguous, fast-evolving environment
• Experience building/supporting agent platforms, AI infrastructure, or internal developer platforms
• Experience building/deploying machine learning or LLM-powered applications in production
• Familiarity with tool calling and LLM application patterns, including:
  • Retrieval-Augmented Generation (RAG)
  • Memory and context management
  • Multi-step workflows and orchestration
  • Human-in-the-loop systems
• Experience designing and implementing evaluation frameworks for LLM/agent quality
• Familiarity with vector databases, model serving, prompt/version management, and experimentation tooling
• Solid knowledge of Data Science principles for NLP
• Experience running services in Kubernetes-based environments
• Strong communication and collaboration skills across engineering, product, and AI teams

Nice-to-haves

• Deep experience with LLM/agent evaluation and experimentation tooling and agent platform operations at scale