Principal Machine Learning Engineer

Role overview

Join Workday as a Principal Machine Learning Engineer in Agent Factory. You will design and build the core ML systems that power the next generation of AI agents, owning production integration across models, agent logic, and orchestration layers.

Responsibilities

• Design and build core machine learning systems for AI agents, including integration of models, agent logic, and orchestration in production.
• Implement and evolve LLM-powered agent frameworks to ensure solutions are scalable, observable, and enterprise-ready.
• Lead and mentor ML Engineering teams, owning the ML development lifecycle and supporting sprint planning.
• Collaborate closely with software engineers, product managers, and data scientists to deliver ML products.

Requirements

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

Nice-to-haves / Focus areas

• Staying current with advancements in LLMs, RAG, autonomous agents, and orchestration frameworks.

Soft skills

• Excellent communication and interpersonal skills with the ability to build strong relationships across stakeholders.