AI Engineer

Join Workday as a Machine Learning Engineer in Agent Factory, where you'll design and build the core ML systems behind the next generation of AI agents. You'll work within a small, senior, cross-functional pod and own the integration of models, agent logic, and orchestration layers in production. This role requires a strong background in machine learning, cloud computing, and experience with large language models.

Responsibilities

• Design and build core machine learning systems for AI agents, overseeing the entire lifecycle from problem framing to deployment.
• Implement and evolve frameworks for LLM-powered agents, ensuring solutions are scalable, observable, and enterprise-ready.
• Collaborate closely with software engineers, product managers, and data scientists to integrate agents into the Workday stack.

Requirements

• Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent
• 5+ years experience as a member of a data science, machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation
• 1+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
• 3+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)
• 3+ years of professional experience in building services to host machine learning models in production at scale
• 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow
• Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
• Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases
• Professional experience in independently solving ambiguous, open-ended problems and technically leading teams
• Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders