Machine Learning Engineer, Workday
CA$128-192k
Enterprise AI platform for managing HR, finance & IT
Job no longer available
Enterprise AI platform for managing HR, finance & IT
1001+ employees
Job no longer available
CA$128-192k
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- You are a strong technical leader with deep Python expertise and solid software engineering skills, capable of writing beautiful, well-designed code while delivering solutions efficiently
- Bachelor’s (Master’s or PhD preferred) degree in engineering, data/computer science, physics, math or equivalent
- 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
- 3+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models
- 3+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)
Desirable
- 3+ years of professional experience in building information retrieval systems and/or graph-based recommendation systems
- 3+ years of hands-on professional experience in developing large language models (LLMs), text generation models, or graph-based machine learning models for production, including data processing, model fine-tuning, model deployment and model evaluation
- 3+ years of professional experience building services to host machine learning models in production at scale
- 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as PySpark, Pytorch, TensorFlow, and Sklearn
- 3+ years of professional experience with data engineering and data wrangling using e.g. Pandas and PySpark and other industry tools used to build scalable machine learning systems, such as Kubernetes and Docker
- 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 team
What the job involves
- The Context and Retrievals team, part of Workday’s AI Platform organization, tackles challenging problems at the intersection of machine learning, agentic reasoning, and enterprise-scale systems
- As a Machine Learning Engineer on the AI Platform Context and Retrievals team, you will develop tailored user experiences using advanced Agentic AI, LLMs and RAG
- You will collaborate with other engineers to deliver ML solutions across Workday’s product ecosystem and use current software and data engineering stacks to enable training, deployment, and lifecycle management of a variety of ML models; supervised and unsupervised
- Additionally, you will develop and deploy new APIs/services using Docker/Kubernetes at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers
- Own exploration, design and implementation of features for our sophisticated ML platforms, pipelines and services
- Be responsible for evaluation, scalability and observability of these features
- Apply machine learning techniques including LLMs and natural language understanding to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud-based machine learning architectures
- Stay up to date with advancements in AI, LLMs, RAG, autonomous agents and orchestration frameworks to drive innovation
- Serve as a technical role model for more junior engineers
Our take
Workday is a cloud-based software vendor that provides management of workforces and finances. The company uses a single database for workforce management and financial management to offer integration and optimize business intelligence across companies. It has added to the packages and tools it offers over the years, providing analytic options that allow companies to combine third-party data with information collected by Workday.
The company has also grown through acquisitions and partnerships to broaden its capabilities. Most recently, in 2025 it purchases Sana, an AI-driven enterprise knowledge and learning platform, to create a "new front door for work". This acquisition allows Workday to integrate Sana's AI-powered search, agents, and learning capabilities with its own data and workflows, allowing employees to access information, automate tasks, and complete their day entirely within Workday.
Through a combination of strategic acquisitions and in-house development, Workday has built a comprehensive suite of HR, financial, and enterprise tools. By focusing on innovation and AI-driven workflows, the company continues to push productivity and decision-making for organizations worldwide. Building on this track record, Workday is very much positioned for even more growth, reinforcing its status as a leader in shaping the future of work.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
16% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Oct 2011
$85m
SERIES F
Apr 2009
$75m
SERIES E
Total funding: $215.3m
Company HQ
Pleasanton, CA
Leadership
Aneel Bhusri
(Co-Founder & CEO)Annel began their career at Morgan Stanley as a Corporate Finance Analyst. They then spent nearly 6 years at PeopleSoft as a Senior VP before co-founding Workday in 2005.
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