Join Workday as a Principal 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 own the integration of models, agent logic, and orchestration layers in production, and work closely with software engineers, product managers, and data scientists. This role requires 10+ years of experience in applied machine learning products, 6+ years of experience with cloud computing platforms, and 3+ years of experience with large language models.
About the role
- 10+ 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 - 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.) - 3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases - Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement - Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent - 6+ years of professional experience in building services to host machine learning models in production at scale - 4+ 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 - Professional experience in independently solving ambiguous, open-ended problems and technically leading teams - Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases - Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholdersKey missions
- Design and build core ML systems for AI agents, overseeing the integration of models, agent logic, and orchestration layers in production.
- Implement and evolve frameworks for LLM-powered agents, ensuring solutions are scalable, observable, and enterprise-ready.
- Lead and mentor ML Engineering teams, taking ownership of the development lifecycle and fostering a culture of collaboration and continuous improvement.