Principal/Senior Machine Learning Engineer

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

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. We work hard, and we're serious about what we do. But we like to have a good time, too. In fact, we run our company with that principle in mind every day: One of our core values is fun.

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. Be part of an innovative, agile force architecting intelligent agents that will revolutionize our customers' workday.

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

Principal Machine Learning Engineer:

Basic Qualifications

• 10+ 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, including taking products through applied research, design, implementation, production, and production-based evaluation

• 4+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow

• 6+ years of professional experience in building services to host machine learning models in production at scale 

• 3+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases

• 6+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)

• Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement

• Bachelor's (Master's or PhD preferred) degree in engineering, computer science, physics, math or equivalent

Senior Machine Learning Engineer:

Basic Qualifications:

• 5+ yrs experience as a member of a machine learning engineering, or other relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation

• 5+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models

• 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface

• 3+ 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.)

• 3+ 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:

• 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

• Proven track record of successfully leading, mentoring, and/or managing ML Engineering teams, taking ownership of development lifecycle and sprint planning; fostering a culture of collaboration, transparency, innovation, and continuous improvement

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.VancouverPrimary Location Base Pay Range: $122,400 CAD - $183,600 CADAdditional US Location(s) Base Pay Range: $167,200 USD - $297,600 USD

Additional Considerations:

If performed in Colorado, the pay range for this job is $176,000 - $264,000 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:
 

11/30/2025

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.

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