Toronto, Ontario, Canada
Onsite
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. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. 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. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.
About the Team
Do you want to build impactful, AI features and solutions that will be used by millions of end-users? We are in the AI Platform organization at Workday and we solve meaningful problems that lie at the intersection of machine learning and enterprise-scale software! We build advanced AI solutions that power the core Workday software by modeling user behavior and providing intelligent automation. Come join us and make it easier and balanced for millions of Workday users!About the Role
We are looking for a Machine Learning Engineer to help design and build our Agent Platform—the core infrastructure that enables teams to develop, deploy, orchestrate, and operate AI agents in production.
This role is focused on building the systems and tooling required to host and scale agent-based applications powered by LLMs. You will work across the platform stack to create reusable capabilities for agent execution, workflow orchestration, observability, evaluation, reliability, and developer experience.
You’ll partner closely with applied AI, product, and infrastructure teams to define how agents are built and operated across the organization. This is an ideal role for someone who enjoys solving hard engineering problems in a fast-evolving technical space and wants to shape the foundation for the next generation of AI applications.
Responsibilities:
Design and build the core platform capabilities required to develop, host, and operate AI agents at scale.
Develop infrastructure and services for agent execution, orchestration, state management, and runtime reliability.
Build reusable abstractions, frameworks, and workflows in Python to support agent development patterns across teams.
Design and implement systems for tool use, memory, retrieval, workflow coordination, and human-in-the-loop interactions.
Build and maintain services deployed on Kubernetes, with a focus on scalability, resiliency, and operational excellence.
Develop capabilities for evaluation, tracing, observability, debugging, and performance monitoring of agent behavior in production.
Improve platform performance across latency, throughput, fault tolerance, and cost efficiency.
Create internal APIs, SDKs, and developer tooling that make it easier for engineering teams to build on the platform.
Partner with cross-functional teams to productionize new agent use cases and establish common platform patterns and best practices.
Contribute to technical architecture and help define the roadmap for agent infrastructure and platform evolution.
About You
Basic Qualifications (MLE III):
3+ yrs experience as part of a data science, machine learning software development team or relevant work in a PhD or equivalent program.
5+ years experience in Python and experience building reliable, maintainable production services.
3+ years experience with distributed systems, APIs, asynchronous workflows, and service-oriented architecture.
3+ years experience designing systems with a focus on scalability, reliability, observability, and maintainability.
Basic Qualifications (Sr. MLE):
6+ years of software engineering experience, including experience building and operating production-grade backend, ML, or platform systems.
8+ years experience in Python and experience building reliable, maintainable production services.
5+ years experience with distributed systems, APIs, asynchronous workflows, and service-oriented architecture.
5+ years experience designing systems with a focus on scalability, reliability, observability, and maintainability
Preferred Qualifications:
Experience building or supporting agent platforms, AI infrastructure, or internal developer platforms.
Experience building and deploying machine learning or LLM-powered applications in production.
Familiarity with LLM application patterns, including:
Tool calling
Retrieval-augmented generation (RAG)
Memory and context management
Multi-step workflows and orchestration
Human-in-the-loop systems
Experience designing and implementing evaluation frameworks for LLM or agent quality.
Familiarity with vector databases, model serving, prompt/version management, and experimentation tooling.
Solid knowledge of Data Science principles and their application in NLP
Experience running services in Kubernetes-based environments.
Ability to work across ambiguity, make strong technical tradeoffs, and drive projects from concept to production.
Strong communication and collaboration skills, with the ability to partner effectively across engineering, product, and AI teams.
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.ON.Toronto
Additional Considerations:
If performed in Colorado, the pay range for this job is $171,600 - $257,400 USD based on min and max pay range for that role if performed in CO.The application deadline for this role is the same as the posting end date stated as below:
Our Approach to Flexible Work
With 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.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
At Workday, we are committed to providing an accessible and inclusive hiring experience where all candidates can fully demonstrate their skills. If you require assistance or an accommodation at any point, please email accommodations@workday.com.
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