Senior Associate Machine Learning 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

It's fun to work in a company where people truly believe in what they're doing. At Workday, we're committed to bringing passion and customer focus to the business of enterprise applications. Would you like to be part of an innovative, agile force architecting intelligent agents that will revolutionize our customers' workday? Join the AI Agent Engineering team, where we're pioneering cutting-edge HR & Finance AI Agents that deeply integrate within the Workday suite.

About the Role

We are seeking highly skilled Machine Learning Engineers to contribute to a cross-functional team building transformative AI agents for HR & Finance. This role is crucial in implementing tooling strategies, staying informed about industry trends, and ensuring our AI-driven solutions integrate effectively within the Workday stack. You will be responsible for implementing AI frameworks, contributing to agent workflow orchestration, utilizing LLMs, agent frameworks, and enterprise AI to design and develop scalable, reliable and trusted AI agents for both HR and Finance.

Key Responsibilities:

• Collaborate with a team of innovative engineers to deliver AI-powered agents that integrate deeply into HR and Financial workflows, accelerating intelligent decision making.
• Develop relationships with software engineers, machine learning engineers, and data scientists on partner teams.
• Apply understanding of the AI system lifecycle, including problem definition, data acquisition, model training, system integration, and validation.
• Implement and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance.
• Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation.
• Work with product, engineering, and data science teams to implement AI-based automation solutions that enhance HR and financial operations.
• Collaborate with external AI vendors, cloud providers, and open-source communities to integrate best-in-class technologies into our AI stack.
• Contribute to establishing monitoring, feedback loops, and continuous learning mechanisms to improve agent performance over time.

About You

Basic Qualifications:

• 3+ years experience as a member of a data science, machine learning / AI engineering, or other relevant software development team building applied machine learning products at scale.
• 2+ years of professional experience with Python, Java, C++, etc. and supporting numeric libraries.
• 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface.
• 1+ years of professional experience in building services to host machine learning models in production at scale with cloud computing platforms (e.g. AWS, GCP, etc.).
• 1+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases.
• Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent.

Other Qualifications:

• 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.
• Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams.