Senior Machine Learning Engineer

Workday is hiring a Senior Machine Learning Engineer in Vancouver, Canada. It pays CAD 156k-CAD 234k a year and Level rates it ; you can apply on Workday.

Level's read on this job

Level rates this machine learning engineer role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include Hugging Face, PyTorch and TensorFlow.
Level classifies it as a senior role.
Level lists 368 other open roles at Workday.
The role was posted in the last few days.

AI in this role

Hugging FacePyTorchTensorFlowscikit-learn

ai-agentsml-opsnlpai-safety

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

At 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 Role

What 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 You

Basic 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.

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 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.

Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.

Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.

If you require a reasonable accommodation, you may email accommodations@workday.com, as far in advance as possible.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

How we rate this

Senior Machine Learning Engineer at Workday rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Machine Learning Engineer is an open job at Workday.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is CAD 156k-CAD 234k a year.
The role is based in Canada, BC, Vancouver.
The job was posted on November 9, 2026.
Seniority: senior.
Applications are handled by Workday. Apply on Workday

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsML OpsNLPAI SafetyHugging FacePyTorchTensorFlowscikit-learn

Also common in machine learning engineer jobs at this level

C++Spark Fine-tuning Azure Reinforcement learning Java

Pay

Typical machine learning engineer job: $198k

Use the typical machine learning engineer figure as a reference when pay comes up. See machine learning engineer jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
How do you monitor a model once it's live, and how do you know it needs retraining?
What NLP problem have you worked on, and how did you measure whether it actually worked?
How do you think about the risk of an AI system in this kind of role failing silently?
Walk me through how you've used Hugging Face in your day-to-day work.

Adapt your resume

List these exact terms on your resume: AI agents, ML Ops, NLP, AI Safety, and Hugging Face. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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