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Job summary

Permanent contract

Canada

Salary: Not specified

Experience: > 5 years

Skills & expertise

AI and machine learning

Communication skills

Problem-solving skills

Workday

TensorFlow

24 days ago

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Questions and answers about the job

As a Machine Learning Engineer in Agent Factory, you’ll design and build the core ML systems behind Workday’s next generation of AI agents. Working within a small, senior, cross-functional pod, you’ll own how models, agent logic, and orchestration layers come together in production—across the full lifecycle from problem framing and data strategy to deployment, monitoring, and continuous improvement
You’ll implement and evolve frameworks for LLM-powered agents, including RAG pipelines, workflow orchestration, evaluation, and feedback loops, ensuring solutions are scalable, observable, and enterprise-ready
This role sits at the intersection of ML and platform engineering: partnering closely with software engineers, product managers, and data scientists to integrate agents deeply into the Workday stack
You’ll stay hands-on with emerging techniques in agentic architectures while applying strong engineering judgment to turn them into systems that are reliable, explainable, and built to operate at global scale

Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent
5+ 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
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
3+ years of proven experience with cloud computing platforms (e.g. AWS, GCP, etc.)
3+ years of professional experience in building services to host machine learning models in production at scale
2+ years of professional experience in machine learning and deep learning frameworks & toolkits such as Pytorch, TensorFlow
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

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