Senior Machine Learning Engineer, Workday
CA$148-222k
Enterprise AI platform for managing HR and finance
Open for applications
Enterprise AI platform for managing HR and finance
1001+ employees
Open for applications
CA$148-222k
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- In addition to contributing to feature and service development, you must have an approach of continuous improvement, passion for quality, scale, and security. Be curious and prepared and question or challenge choices and practices where they don't make sense or could be improved. e
- Having a product approach and strong intuition around how ML can drive a better customer experience. Also, a strong sense of ownership and teamwork are crucial to succeed in this rol
- Bachelor’s (Master’s or PhD preferred) degree in engineering, computer science, physics, math or equivalent
- 5+ 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
- 5+ years of professional experience with Python and supporting numeric libraries, with experience in shipping production code and models
- 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 text-based 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 working with large language models (LLMs), text generation models, and/or graph neural network models for real-world use cases
- 3+ years of professional experience in machine learning and deep learning frameworks & toolkits such as 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
- 3+ years of professional experience with cloud computing platforms (e.g. AWS, GCP, etc.)
- 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
- Standout colleague, strong communication skills, with experience working across functions and teams. Ability to teach, mentor and lead through influence
- Bonus points for relevant PhD and/or machine learning related research publications
What the job involves
- We are developing ML-powered Information Retrieval, Recommendation and Agentic services and platforms to modernize and simplify user interactions with Workday. As a senior machine learning engineer, you will help develop tailored user experiences using advanced Agentic AI, LLMs, Knowledge Graphs, personalization, and predictive analysis.
- 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, and agentic AI powered by LLMs.
- Additionally, you will develop and deploy new APIs/microservices using docker/kubernetes at scale and leverage Workday’s vast computing resources on rich datasets to deliver transformative value to our customers. Sound like your kind of challenge?
- Own exploration, design and execution of sophisticated ML models, algorithms and frameworks that deliver value to our users
- Apply machine learning techniques including LLMs, knowledge graphs, deep learning including generative models, natural language understanding, topic modeling and named entity recognition to analyze large sets of HR and Finance-related text data, and design and launch pioneering cloud-based machine learning architectures
- Be responsible for the performance, scalability, metric based deployed evaluation, and ongoing data driven enhancements of the products
- Stay on top of the latest advancements in NLP research, techniques, and tools and apply this knowledge to ML Features. Serve as a technical role model for more junior engineers
- Respond to alerts and debug production issues as part of on-call rotation
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 & Executive Chair)Annel began his career at Morgan Stanley as a Corporate Finance Analyst. He then spent nearly 6 years at PeopleSoft as a Senior VP before co-founding Workday in 2005, where he has served as the CEO ever since.
Carl Eschenbach
(CEO)Carl joined Workday in 2022 as Co-CEO, becoming CEO in 2024. He has also been a Partner at Sequoia Capital since 2016. Previously, he spent 14 years at VMware as President and COO and 3 years at Inktomi Corporation as the VP of North America Sales.
Peter Bailis
(CTO)Prior to joining Workday in 2025, People was a VP of Engineering at Google. He also previously founded Sisu Data, where he served as the CEO for over 5 years.
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