Principal Machine Learning Engineer

Role Overview

Join Workday as a Principal Machine Learning Engineer in Agent Factory, where you will design and build the core machine learning systems behind the next generation of AI agents. You will own model integration, agent logic, and orchestration layers deployed in production, collaborating closely with software engineers, product managers, and data scientists.

Key Missions / Responsibilities

• Design and build core ML systems for AI agents, including integration of models, agent logic, and orchestration layers in production.
• Implement and evolve LLM-powered agent frameworks that are scalable, observable, and enterprise-ready.
• Lead and mentor ML Engineering teams, owning the development lifecycle and fostering collaboration, transparency, innovation, and continuous improvement.

Requirements

• 10+ years experience building applied machine learning products at scale, covering the full lifecycle: applied research, design, implementation, production, and production-based evaluation.
• 6+ years experience with cloud computing platforms (e.g., AWS, GCP).
• 3+ years experience with large language models (LLMs) and/or related text generation or graph neural network models for real-world use cases.
• Experience leading and mentoring/managing ML engineering teams, including ownership of development lifecycle and sprint planning.
• Bachelor’s degree (Master’s or PhD preferred) in Engineering, Computer Science, Physics, Math, or equivalent.
• 6+ years building services to host ML models in production at scale.
• 4+ years with machine learning & deep learning frameworks such as PyTorch and TensorFlow.
• Ability to independently solve ambiguous, open-ended problems and technically lead teams.
• Strong understanding of statistical analysis, supervised/unsupervised ML, and NLP for information retrieval and/or recommendation systems.
• Excellent communication and stakeholder management skills.

Nice to Have

• Stay current on advancements in AI, LLMs, RAG, autonomous agents, and orchestration frameworks.