Machine Learning Engineer Iii

Workday

Pleasanton, CA, USA
Base: $160,000 - $240,000 usd; bonus/equity: eligi...
Hybrid (at least 50% in-office time quarterly)
3+ years production ml systems experience
Deep learning and nlp expertise
Rag architectures and agentic frameworks
Workday is seeking a Machine Learning Engineer III to join their AI Platform team in Pleasanton, CA. The role focuses on developing and optimizing agentic AI, semantic parsing, and information retrieval products, contributing to the company's innovative work culture and commitment to employee development

Job Summary

  • This role involves architecting sophisticated reasoning, planning, and swarm agents that interact seamlessly with enterprise data to drive Workday's AI transformation.
  • Candidates will leverage exclusive high-integrity enterprise datasets to solve complex technical challenges at the frontier of Agentic AI and semantic parsing.
  • The position offers a people-first culture balancing high-intensity innovation with sustainable work-life integration and full ownership of end-to-end MLOps processes.

Matching Summary

Match Score: 85

Workday is seeking a Machine Learning Engineer III to join their AI Platform team in Pleasanton, CA. The role focuses on developing and optimizing agentic AI, semantic parsing, and information retrieval products, contributing to the company's innovative work culture and commitment to employee development.

Salary

Base: $160,000 - $240,000 USD; Bonus/Equity: Eligible for Workday Bonus Plan and annual refresh stock grants; Benefits: Comprehensive benefits package including flexible work options

Skills & Requirements

Must-have

  • 3+ years production ML systems experience
  • Deep learning and NLP expertise
  • RAG architectures and agentic frameworks
  • Python with asynchronous patterns
  • PyTorch or TensorFlow proficiency
  • Cloud-native deployment (Docker/K8s)
  • A/B testing and model evaluation

Nice-to-have

  • DSPy and Reinforcement Learning knowledge
  • Graph neural networks experience
  • Multi-modal models background
  • Peer-reviewed research publications
  • Cross-functional team leadership
  • Mentoring junior engineers
  • High autonomy in problem solving

Key Requirements

  • Master's or Ph.D. in quantitative field
  • 3+ years researching and deploying ML systems
  • 2+ years Python experience with scalable architecture
  • Experience with LLM-powered products and RAG
  • Proficiency in large-scale data processing (PySpark)

Work Rights

Not specified

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