Workday

Workday is seeking a Principal Machine Learning Engineer to design and build core ML systems for AI agents. This role involves owning the full lifecycle of LLM-powered agents, including RAG pipelines, orchestration, evaluation, and deployment within Workday's platform. The position requires strong engineering judgment, collaboration with cross-functional teams, and experience with large-scale ML systems.

Workday is seeking a Senior Machine Learning Engineer to join their AI Team in Canada. The role involves architecting, building, and deploying scalable ML models and AI systems, including predictive models, Generative AI, and LLM-powered agents, impacting Workday's core enterprise applications. The engineer will own the end-to-end ML lifecycle, collaborate with cross-functional teams, drive technical excellence, mentor junior engineers, and champion Responsible AI. Requires 7+ years of experience in applied ML/DL/NLP, Python proficiency, experience with ML frameworks (PyTorch, TensorFlow), production deployment, and cloud platforms (AWS/GCP).

Workday is seeking a Machine Learning Engineer to build their Agent Platform, focusing on the infrastructure for hosting and scaling LLM-powered agent applications. The role involves developing systems for agent execution, orchestration, observability, evaluation, and reliability, working closely with applied AI, product, and infrastructure teams to define how agents are built and operated.

Senior Machine Learning Engineer on the AI Core team, responsible for designing, building, and deploying novel agentic systems and core machine learning models for AI-driven applications at Workday. This role involves end-to-end MLOps, working with large-scale datasets, and applying ML and distributed systems principles in production.

Machine Learning Engineer role focused on developing and deploying AI-first products for Document Intelligence and Contract Intelligence, leveraging LLMs, Knowledge Graphs, and predictive analysis. The role involves building ML solutions at scale within Workday's product ecosystem, with a focus on continuous improvement, product intuition, and customer experience.

Senior Software Development Engineer on the AI Core team, responsible for designing, building, and operating software systems for AI-powered agentic applications. Focuses on building agentic tooling for information retrieval using ML RAG platforms, with an emphasis on enterprise-scale systems for retrieval and recommendation use cases.

This Principal Software Engineer role focuses on building and scaling MLOps and CloudOps infrastructure for Workday's AI platform. The engineer will design and implement microservices, APIs, and cloud infrastructure using Python, Go, Terraform, and Kubernetes, with a focus on enabling the development, training, deployment, and lifecycle management of ML capabilities. The role also involves supporting Agentic AI systems and LLM-based applications, requiring experience with distributed systems, cloud computing, and infrastructure-as-code.

Engineering Manager to lead a team building the Agent Platform, which is the core infrastructure for developing, deploying, orchestrating, and operating AI agents in production. The role involves leading engineers on backend services, distributed systems, and developer tooling, driving execution, shaping technical direction, and building a high-performing team.

This role focuses on product specialization within Legal AI, specifically for contract management. It involves crafting and maintaining datasets for legal models, collaborating with Product Managers and Data Science teams, identifying automation use cases, and becoming a subject matter expert in contracts. The role requires experience with generative AI and LLMs, and analyzing large volumes of legal data.

Product Manager role focused on the delivery of AI-powered agents, either customer-facing or building the underlying infrastructure and frameworks for Workday's application teams. The role involves experimentation, innovation, development, iteration, and scaling of these agents, requiring close collaboration with domain-specific Product Managers to maximize technological impact and drive business value.