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Machine Learning Engineer/Senior Machine Learning Engineer - Evisort
About the Role
As a Machine Learning Engineer, you will help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis. You will collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem and utilize software and data engineering stacks to enable training, deployment, and lifecycle management of various ML models. You will develop and deploy new products at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers. In addition to contributing to feature and service development, you must approach continuous improvement, prioritize quality, scale and security, and maintain a product mindset to drive better customer experience. Ownership and teamwork are essential in this role. Responsibilities
Build and deploy machine learning models at scale. Develop services for hosting models in production. Work with large language models, text generation, and graph neural networks for real-world use cases. Leverage cloud platforms such as AWS and GCP for model training and inference. Collaborate with cross‑functional teams to deliver ML solutions across product ecosystems. Champion continuous improvement and quality, ensuring secure and scalable deployments. Basic Qualifications
5+ years of experience as a member of a data science, machine learning engineering, or relevant software development team building applied machine learning products at scale, including research, design, implementation, production, and evaluation. 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as PyTorch, TensorFlow. 2+ years of professional experience building services to host machine learning models in production at scale. 2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases. 2+ years of proven experience with cloud computing platforms (e.g. AWS, GCP). Bachelor’s degree in engineering, computer science, physics, math or equivalent; Master’s or PhD preferred. Senior MLE Qualifications
6+ years of experience in building applied machine learning products at scale, including research, design, implementation, production, and evaluation. 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as PyTorch, TensorFlow. 3+ years of professional experience 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. 3+ years of proven experience with cloud computing platforms (e.g. AWS, GCP). Bachelor’s degree in engineering, computer science, physics, math or equivalent; Master’s or PhD preferred. Other Qualifications
Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks. Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and recommendation systems. 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. This role may be eligible for the Workday Bonus Plan or a role‑specific commission/bonus, as well as annual refresh stock grants. Compensation will be based on multiple factors including geography, experience, skills, job duties, and business need. Primary Location
CAN.BC.Vancouver. Base pay range: $128,000 CAD – $192,000 CAD. EEO Statement
Workday is an Equal Opportunity Employer, including individuals with disabilities and protected veterans. We are committed to providing an accessible and inclusive hiring experience. Qualified applicants with arrest and conviction records are considered under applicable Fair Chance law.
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As a Machine Learning Engineer, you will help develop tailored user experiences using advanced LLMs, Knowledge Graphs, personalization, and predictive analysis. You will collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem and utilize software and data engineering stacks to enable training, deployment, and lifecycle management of various ML models. You will develop and deploy new products at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers. In addition to contributing to feature and service development, you must approach continuous improvement, prioritize quality, scale and security, and maintain a product mindset to drive better customer experience. Ownership and teamwork are essential in this role. Responsibilities
Build and deploy machine learning models at scale. Develop services for hosting models in production. Work with large language models, text generation, and graph neural networks for real-world use cases. Leverage cloud platforms such as AWS and GCP for model training and inference. Collaborate with cross‑functional teams to deliver ML solutions across product ecosystems. Champion continuous improvement and quality, ensuring secure and scalable deployments. Basic Qualifications
5+ years of experience as a member of a data science, machine learning engineering, or relevant software development team building applied machine learning products at scale, including research, design, implementation, production, and evaluation. 2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as PyTorch, TensorFlow. 2+ years of professional experience building services to host machine learning models in production at scale. 2+ years of demonstrated experience working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases. 2+ years of proven experience with cloud computing platforms (e.g. AWS, GCP). Bachelor’s degree in engineering, computer science, physics, math or equivalent; Master’s or PhD preferred. Senior MLE Qualifications
6+ years of experience in building applied machine learning products at scale, including research, design, implementation, production, and evaluation. 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as PyTorch, TensorFlow. 3+ years of professional experience 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. 3+ years of proven experience with cloud computing platforms (e.g. AWS, GCP). Bachelor’s degree in engineering, computer science, physics, math or equivalent; Master’s or PhD preferred. Other Qualifications
Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks. Deep understanding of statistical analysis, unsupervised and supervised machine learning algorithms, and natural language processing for information retrieval and recommendation systems. 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. This role may be eligible for the Workday Bonus Plan or a role‑specific commission/bonus, as well as annual refresh stock grants. Compensation will be based on multiple factors including geography, experience, skills, job duties, and business need. Primary Location
CAN.BC.Vancouver. Base pay range: $128,000 CAD – $192,000 CAD. EEO Statement
Workday is an Equal Opportunity Employer, including individuals with disabilities and protected veterans. We are committed to providing an accessible and inclusive hiring experience. Qualified applicants with arrest and conviction records are considered under applicable Fair Chance law.
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