Senior Machine Learning Engineer, Workday
CA$156-234k
More information about location
2-3 days a week in office
Enterprise AI platform for managing HR and finance
Be an early applicant
Enterprise AI platform for managing HR and finance
1001+ employees
Be an early applicant
CA$156-234k
More information about location
2-3 days a week in office
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 expertise in machine learning, agentic systems, and Python, capable of writing production-grade code while delivering solutions efficiently
- 8+ years of professional Machine Learning / AI engineering experience, including designing, building, and scaling production ML models and systems
- 5+ years of experience with advanced Python development
- Bachelor’s degree in Computer Science, Machine Learning, or related discipline, or equivalent practical experience
- Expertise in designing, training, and evaluating Machine Learning models (e.g., LLMs, deep learning models, classical ML) and deploying them to production environments
- Expertise with building agentic systems and leveraging LLMs, retrieval-augmented generation (RAG), and sophisticated prompting techniques
- Proficiency with popular Machine Learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and MLOps tools
- Strong understanding of data wrangling, feature engineering, and data validation techniques for large-scale datasets
- Proficiency with advanced Python concepts, such as asynchronous and concurrent programming, generators, higher-order abstractions, and applying object-oriented design principles
- Proficiency with unix systems and cloud platforms, including containerized workloads and orchestration systems (e.g., AWS or GCP, Docker, Kubernetes)
- Ability to collaborate effectively across teams, working closely with other engineers while maintaining independent execution
- Ownership mindset, able to take responsibility for a work area and deliver high-quality, reliable systems
- Ability to mentor and coach other engineers, promoting best practices and raising the engineering bar
- Architectural thinking skills, with the ability to contribute meaningful ideas and practical solutions in design and architecture discussions
- Ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders
What the job involves
- Do you want to build AI-powered software that impacts millions of people every day? The AI Core team, part of Workday’s AI Platform organization, tackles challenging problems at the intersection of machine learning, agentic reasoning, and enterprise-scale systems. Our work delivers critical AI platform capabilities and differentiated, deep-value agent applications
- As a Senior Machine Learning Engineer on the AI Core team, you will be primarily responsible for designing, building, and applying machine learning models and agentic systems that power AI-driven applications at Workday. Specifically, you will:
- Lead the design, development, and deployment of novel agentic systems and core machine learning models that power AI-driven capabilities
- Execute data analysis, error analysis, and rigorous experimentation to drive model improvements and new capability development
- Design and implement the end-to-end machine learning pipeline (MLOps), ensuring model scalability, reliability, and consumption via robust APIs
- Work with large-scale datasets to perform data wrangling, feature engineering, and validation to train and fine-tune state-of-the-art models
- Apply machine learning and distributed systems principles in production to address model scalability, concurrency, fault tolerance, and performance challenges
- Own ML models and systems through their full lifecycle, including deployment, monitoring, debugging, and ongoing operational improvements
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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