Workday is looking to solve the problem of building intelligent agents used by millions of people every day, by forming small, senior, cross-functional AI teams to create production-grade AI deeply embedded into Workday’s platform
Requirements
- 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
- 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.)
- 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
Responsibilities
- Design and build the core ML systems behind Workday’s next generation of AI agents
- Own how models, agent logic, and orchestration layers come together in production—across the full lifecycle from problem framing and data strategy to deployment, monitoring, and continuous improvement
- Implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops
- Ensure solutions are scalable, observable, and enterprise-ready
- Partner closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack
- 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
- Take ownership of development lifecycle and sprint planning
Other
- Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent
- Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning
- Excellent interpersonal and communication skills, with the ability to build strong relationships across teams and stakeholders
- Must spend at least half (50%) of time each quarter in the office or in the field with customers, prospects, and partners
- Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records
