AI Engineer in Vancouver

Your work days are brighter here. We’re 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, we’re shaping the future of work so teams can reach their potential and focus on what matters most. Our culture is rooted in integrity, empathy, and shared enthusiasm. We look for curious minds and courageous collaborators who bring sun‑drenched optimism and drive.

About the Team: Agent Factory is where Workday’s next chapter gets built. We’re 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 AI—deeply embedded into Workday’s platform. Teams own problems end to end, collaborate tightly across disciplines, and use the right tools to solve real customer challenges at global scale.

About the Role: As a Machine Learning Engineer in Agent Factory, you’ll design and build the core ML systems behind Workday’s next generation of AI agents. You’ll 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. You’ll implement and evolve frameworks for LLM‑powered agents, 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.

Basic Qualifications:

• 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.
• 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow.
• 3+ years of professional experience in building services to host machine learning models in production at scale.
• 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.).
• Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent.

Other Qualifications:

• 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.