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Senior Associate Machine Learning Engineer

Canada, BC, Vancouver

Pay
CAD 100,000–150,000/year · BaseAnnual period assumed — pay source
Primary Location: CAN.BC.Vancouver Primary CAN Base Pay Range: $100,000 - $150,000 CAD Additional CAN Location(s) Base Pay Range: $100,000 - $150,000 CAD
Primary CAN Base Pay Range: $100,000 - $150,000 CAD Additional CAN Location(s) Base Pay Range: $100,000 - $150,000 CAD Our Approach to Flexible Work
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Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full Time
From the employer’s posting
Apply at Workday

What you’ll work on

Full posting

We are seeking highly skilled Machine Learning Engineers to contribute to a cross-functional team building transformative AI agents for HR & Finance.

  • Develop AI agents that integrate into HR and financial workflows

  • Implement AI tools, frameworks and platforms for scalability and compliance

  • Contribute to agent workflow orchestration using LLMs and agent frameworks

  • Build monitoring and feedback loops to improve agent performance over time

  • Integrate external AI vendors and open-source technologies into the AI stack

From the employer’s posting
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.
Collaborate with a team of innovative engineers to deliver AI-powered agents that integrate deeply into HR and Financial workflows
Implement and integrate AI tools, frameworks, and platforms to ensure scalability, efficiency, and compliance.
contributing to agent workflow orchestration, utilizing LLMs, agent frameworks, and enterprise AI
Contribute to establishing monitoring, feedback loops, and continuous learning mechanisms to improve agent performance over time.
Collaborate with external AI vendors, cloud providers, and open-source communities to integrate best-in-class technologies into our AI stack.

What you’ll bring

All qualifications

Core experience

  • 3+ years experience as a member of a data science, machine learning / AI 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
  • Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases
  • 2+ years of professional experience with Python, Java, C++, etc.
  • 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface
  • 1+ years of professional experience in building services to host machine learning models in production at scale with cloud computing platforms (e.g.
  • 1+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
Qualification wording
3+ years experience as a member of a data science, machine learning / AI 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
Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation system use cases
2+ years of professional experience with Python, Java, C++, etc. and supporting numeric libraries, with experience in shipping production code and models
1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface
1+ 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.)
1+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
Education & alternatives
- 1+ 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:

Tools in this posting

  • Java
  • Python
  • AWS
  • GCP
  • Hugging Face
  • PyTorch
  • TensorFlow
  • C++
Source — Tool mentions in context
- 3+ years experience as a member of a data science, machine learning / AI 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 - 2+ years of professional experience with Python, Java, C++, etc. and supporting numeric libraries, with experience in shipping production code and models - 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface
- 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface - 1+ 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.) - 1+ years of professional experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
- 2+ years of professional experience with Python, Java, C++, etc. and supporting numeric libraries, with experience in shipping production code and models - 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface - 1+ 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.)

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Status in our records
Live
First seen by us
Sep 30, 2026 · 30 days ago
Recorded sightings
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Last seen by us
Oct 30, 2026

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Job description

View original posting ↗

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

Basic Qualifications:

  • 3+ years experience as a member of a data science, machine learning / AI 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
  • 2+ years of professional experience with Python, Java, C++, etc. and supporting numeric libraries, with experience in shipping production code and models
  • 1+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow, Huggingface
  • 1+ 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.)
  • 1+ 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, etc.


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: $100,000 - $150,000 CAD

Additional CAN Location(s) Base Pay Range: $100,000 - $150,000 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.

Source details

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Pay
Primary Location: CAN.BC.Vancouver Primary CAN Base Pay Range: $100,000 - $150,000 CAD Additional CAN Location(s) Base Pay Range: $100,000 - $150,000 CAD
More source context
Primary CAN Base Pay Range: $100,000 - $150,000 CAD Additional CAN Location(s) Base Pay Range: $100,000 - $150,000 CAD Our Approach to Flexible Work
Location & working pattern

Canada, BC, Vancouver

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.
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