Senior Machine Learning Engineer - AI Platform

Workday • Vancouver, BC

18h • $163,000 - $288,000 • Hybrid

About The Position

The Senior Machine Learning Engineer will join Workday’s AI Core team within the AI Platform organization, building AI-powered software and platform capabilities for Workday products. The role develops tailored user experiences using agentic AI, large language models (LLMs), and retrieval-augmented generation (RAG), and collaborates with engineers to deliver machine learning solutions across Workday’s product ecosystem. It uses current software and data engineering stacks to support training, deployment, and lifecycle management of supervised and unsupervised models, and develops and deploys APIs and services using Docker and Kubernetes at scale.

The engineer will explore, design, and implement features for machine learning platforms, pipelines, and services, and be responsible for their evaluation, scalability, and observability. The role applies machine learning, LLMs, and natural language understanding to large HR- and Finance-related text datasets, and designs and launches cloud-based machine learning architectures. It also requires staying current with AI, LLM, RAG, autonomous agent, and orchestration developments, and serving as a technical role model for junior engineers.

Requirements

• Bachelor’s degree in engineering, data science, computer science, physics, mathematics, or equivalent.
• At least 6 years of experience on a data science, machine learning engineering, or relevant software development team building applied machine learning products at scale, including taking products through applied research, design, implementation, production, and production-based evaluation.
• At least 5 years of professional Python experience, including supporting numeric libraries and shipping production code and models.
• At least 5 years of professional experience with cloud computing platforms such as AWS or GCP.
• At least 3 years of experience building information retrieval systems and/or graph-based recommendation systems.
• At least 3 years of hands-on professional experience developing LLMs, text-generation models, or graph-based machine learning models for production, including data processing, fine-tuning, deployment, and evaluation.
• At least 3 years of experience building services to host machine learning models in production at scale.
• At least 3 years of experience with machine learning and deep learning frameworks and toolkits such as PySpark, PyTorch, TensorFlow, and Scikit-learn.
• At least 3 years of professional experience with data engineering and data wrangling using tools such as Pandas and PySpark, and building scalable machine learning systems with tools such as Kubernetes and Docker.
• Deep understanding of statistical analysis, supervised and unsupervised machine learning algorithms, and natural language processing for information retrieval and/or recommendation use cases.
• Professional experience independently solving ambiguous, open-ended problems and technically leading teams.
• Ability to communicate clearly and effectively with product managers, application teams, and leadership in cross-functional settings.

Nice To Haves

• Master’s or PhD degree in engineering, data science, computer science, physics, mathematics, or equivalent.

Responsibilities

• Own exploration, design, and implementation of features for machine learning platforms, pipelines, and services.
• Ensure feature evaluation, scalability, and observability.
• Apply machine learning, LLMs, and natural language understanding to large HR- and Finance-related text datasets.
• Design and launch cloud-based machine learning architectures.
• Develop and deploy APIs and services using Docker and Kubernetes at scale.
• Support model training, deployment, and lifecycle management across supervised and unsupervised machine learning models.
• Keep up with developments in AI, LLMs, RAG, autonomous agents, and orchestration frameworks to drive innovation.
• Serve as a technical role model for more junior engineers.
• Collaborate with engineers and cross-functional partners to deliver machine learning solutions across Workday’s product ecosystem.

Benefits

• May be eligible for the Workday Bonus Plan or a role-specific commission/bonus.
• May be eligible for annual refresh stock grants.
• Workday comprehensive benefits are referenced; specific benefits are not listed in the posting.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior