Base: $156,000 - $234,000 cad; bonus/equity: role ...
On-site
Design, develop, and deploy scalable machine learning models
End-to-end ownership of ml lifecycle
Partner closely with cross-functional teams
We’re building the intelligence layer that powers the future of work for millions of global users, embedding cutting-edge machine learning, Generative AI, and autonomous agents directly into Workday's core platform
Job Summary
We’re building the intelligence layer that powers the future of work for millions of global users, embedding cutting-edge machine learning, Generative AI, and autonomous agents directly into Workday's core platform.
As part of our team, you will operate at the intersection of deep applied research and scalable engineering, leveraging Workday's massive, clean, and exclusive datasets to deliver features that accelerate human workflows.
In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul.
Matching Summary
We’re building the intelligence layer that powers the future of work for millions of global users, embedding cutting-edge machine learning, Generative AI, and autonomous agents directly into Workday's core platform.
Salary
Base: $156,000 - $234,000 CAD; Bonus/Equity: role may be eligible for bonus plan or commission/bonus, annual refresh stock grants; Benefits: comprehensive benefits
Skills & Requirements
Must-have
design, develop, and deploy scalable machine learning models
end-to-end ownership of ML lifecycle
partner closely with cross-functional teams
establish and advocate for engineering best practices
expert-level proficiency in Python
deep hands-on experience with ML/DL libraries
proven track record of production deployment
solid experience with cloud computing platforms
Nice-to-have
curious minds and courageous collaborators
sun-drenched optimism and drive
building smarter solutions
transition emerging AI capabilities
principles of Responsible AI
Key Requirements
7+ years of industry experience in software engineering
Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related field (or equivalent practical experience)
Expert-level proficiency in Python
Deep hands-on experience with PyTorch, TensorFlow, Scikit-learn, Hugging Face
Solid experience with AWS or GCP, Docker, Kubernetes