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

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 scale

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.)

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 . Primary Location: CAN.BC.VancouverPrimary Location Base Pay Range: $122,400 CAD - $183,600 CADAdditional US Location(s) Base Pay Range: $139,800 USD - $248,400 USD Additional Considerations: If performed in Colorado, the pay range for this job is $147,200 - $220,800 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:

08/08/2025