About the TeamAt Workday AI Team, we are building the intelligence layer that powers the future of work for millions of global users. Our AI organization is responsible for seamlessly embedding cutting-edge machine learning, Generative AI, and autonomous agents directly into Workday's core platform-optimizing the HR and financial operations of some of the world's largest enterprises. We don't just run sandbox experiments; we build robust, production-grade AI solutions that solve real business challenges at global scale. As part of our team, you will operate at the intersection of deep applied research and scalable engineering. Whether we are developing sophisticated LLM-powered agents, advancing our next-generation AI engine (Workday Illuminate), or engineering highly precise information retrieval and recommendation systems, we leverage Workday's massive, clean, and exclusive datasets to deliver features that accelerate human workflows. We are a highly collaborative, cross-functional group of product leaders, data scientists, and ML engineers committed to the principles of Responsible AI. If you are a curious, courageous builder who wants to transition emerging AI capabilities into high-impact enterprise realities, you'll find a home with us.
About the RoleWhat you will do:
- Architect & Build: Design, develop, and deploy scalable machine learning models and AI systems (ranging from predictive models to Generative AI and LLM-powered agents) that directly impact Workday's core enterprise applications.
- End-to-End Ownership: Take full ownership of the ML lifecycle, including data extraction, feature engineering, model training, deployment, optimization, and continuous monitoring in a high-scale production environment.
- Cross-Functional Collaboration: Partner closely with Data Scientists, Software Engineers, Product Managers, and UX Designers to translate complex business problems into robust AI solutions.
- Drive Technical Excellence: Establish and advocate for engineering best practices, robust MLOps processes, and highly optimized code.
- Mentorship & Leadership: Guide and mentor junior engineers, conduct code and architecture reviews, and help shape the technical roadmap for your team.
- Champion Responsible AI: Ensure all models adhere to Workday's strict standards for data privacy, security, fairness, and ethical AI practices.
About YouBasic Qualifications (Sr Machine Learning Engineer)
- Experience: 7+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP.
- Programming Mastery: Expert-level proficiency in Python and strong software engineering fundamentals (data structures, algorithms, object-oriented design).
- ML Frameworks: Deep hands-on experience with industry-standard machine learning and deep learning libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face).
- Production Deployment: Proven track record of taking ML models out of research/notebook environments and deploying them into scalable, high-traffic production systems.
- Cloud & Infrastructure: Solid experience with cloud computing platforms (AWS or GCP) and modern infrastructure tools (Docker, Kubernetes).
- Education: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related highly quantitative field (or equivalent practical experience).
Basic Qualifications (Machine Learning Engineer)
- Experience: 5+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP.
- Programming Mastery: Expert-level proficiency in Python and strong software engineering fundamentals (data structures, algorithms, object-oriented design).
- ML Frameworks: Deep hands-on experience with industry-standard machine learning and deep learning libraries (e.g., PyTorch, TensorFlow, Scikit-learn, Hugging Face).
- Production Deployment: Proven track record of taking ML models out of research/notebook environments and deploying them into scalable, high-traffic production systems.
- Cloud & Infrastructure: Solid experience with cloud computing platforms (AWS or GCP) and modern infrastructure tools (Docker, Kubernetes).
- Education: Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related highly quantitative field (or equivalent practical experience).
Workday Pay Transparency Statement The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate's compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday's comprehensive benefits, please click here.
Primary Location: CAN.BC.Vancouver
Primary CAN Base Pay Range: $156,000 - $234,000 CAD
Additional CAN Location(s) Base Pay Range: $156,000 - $234,000 CAD
Our Approach to Flexible WorkWith Flex Work, we're combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply
spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
