Principal/Senior/Machine Learning Engineer III
Canada, BC, Vancouver
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Full Time Senior-level / Expert USD 122K - 183K
Workday
Workday unites HR and finance on one AI platform to help elevate humans and supercharge work to keep business moving forever forward.Your work days are brighter here.
At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. Thatās why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you donāt need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.
At Workday, we value our candidatesā privacy and data security.Ā Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.Ā
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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.
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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.
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.Ā
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 scaleĀ
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
Bachelorās (Masterās 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
Bachelorās (Masterās or PhD preferred) degree in engineering, computer science, physics, math or equivalent
Machine Learning Engineer III:
Basic Qualifications
3+ yrs 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
1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow
1+ years of professional experience in building services to host machine learning models in production at scaleĀ
1+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
1+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)
Bachelorās (Masterās 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
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 candidateās 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 Workdayās comprehensive benefits, please click here.
Primary Location: CAN.BC.VancouverPrimary Location Base Pay Range: $122,400 CAD - $183,600 CADPrimary CAN Base Pay Range: $122,400 - $183,600 CAD
Our Approach to Flexible Work
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With Flex Work, weāre 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.
Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!
Tags: Agile AWS CAD Computer Science Consulting Deep Learning Engineering Finance GCP HuggingFace LLMs Machine Learning Mathematics ML models Model training NLP Open Source PhD Physics Privacy Python PyTorch RAG Research Security Statistics TensorFlow
Perks/benefits: Career development Flex hours Home office stipend Salary bonus Transparency
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