
Principal Machine Learning Engineer
NEW YORK, NYJobSeen 5 days agoSeen in employer's feed 5 days ago
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Job overview
Workday’s Agent Factory builds production-grade AI agents embedded in its platform. The Principal Machine Learning Engineer designs and builds core ML systems for those agents, owning the lifecycle from problem framing and data strategy through deployment, monitoring, and improvement. The role develops LLM-agent frameworks and partners with software engineers, product managers, and data scientists to integrate scalable, observable, enterprise-ready systems into Workday.
Skills & qualifications
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Full job description
Your work days are brighter here.Were obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, were shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, youll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. Were in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, youll do meaningful work with Workmates whove got your back. In return, well give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, youve found a match in Workday, and we hope to be a match for you too.About the TeamAgent Factory is where Workdays next chapter gets built. Were forming small, senior, cross-functional AI teams that bring together product leaders, machine learning engineers, and full-stack builders to create intelligent agents used by millions of people every day. This is production-grade AIdeeply embedded into Workdays platformnot research experiments or maintenance work. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale. Youll work at the intersection of AI, platform architecture, and human workflows, with the autonomy to shape how agents reason, act, and scale responsibly. High trust, high expectations, and real impact. Engineering, but brighter.About the RoleAs a Principal Machine Learning Engineer in Agent Factory, youll design and build the core ML systems behind Workdays next generation of AI agents. Working within a small, senior, cross-functional pod, youll own how models, agent logic, and orchestration layers come together in productionacross the full lifecycle from problem framing and data strategy to deployment, monitoring, and continuous improvement. Youll implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops, ensuring solutions are scalable, observable, and enterprise-ready. This role sits at the intersection of ML and platform engineering: partnering closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack. Youll stay hands-on with emerging techniques in agentic architectures while applying strong engineering judgment to turn them into systems that are reliable, explainable, and built to operate at global scale.About YouBasic Qualifications * 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 * 4+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow * 6+ years of professional experience in building services to host machine learning models in production at scale * 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 * 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.) * Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering
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