MLOps Software Engineer, Workday
CA$106.4-159.6k
Enterprise AI platform for managing HR and finance
Job no longer available
Enterprise AI platform for managing HR and finance
1001+ employees
Job no longer available
CA$106.4-159.6k
1001+ employees
Company mission
To leverage the power of AI to elevate humans and supercharge work, moving business forever forward.
Role
Who you are
- 5 or more years of validated industry experience
- Bachelor’s and/or Master’s degree in Computer Science or Computer Engineering
- Professional experience in building web applications and microservices and API design
- Experience in supporting large Kubernetes networks in production
- 5 or more years of cloud programming experience preferably in Python or Go
- Experience with running and maintaining Databricks, Sagemaker, & Apache Spark as a service
- Implementation and operation of distributed systems and software development including the conception, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components
- Experience in managing relevant tools like Databricks and Sagemaker to perform efficient computation and management of large scale data lakes
- Experience of data and/or ML systems with ability to think across layers of the stack
- Develop and maintain monitoring and alerting systems for proactively identifying and addressing issues within the machine learning infrastructure
- Experience in leading or mentoring other team members and proven team collaboration experience, i.e. understanding group dynamics, effective communication strategies, conflict resolution techniques, and the ability to foster a positive and inclusive team environment
What the job involves
- This is an opportunity to be part of a growth team focused on MLOps
- We build ML capabilities into our products, and you would be building part of the next generation of Workday technology
- As a Software Engineer you will help develop ML powered features and experiences for every user across our HR & Talent product portfolio
- You will work closely with ML engineers and other software teams to deliver critically important infrastructure and software frameworks that enable machine learning across Workday’s product ecosystem
- You will apply modern MLOps, CloudOps, and data engineering stacks to enable development, training, deployment, and lifecycle management of a variety of ML capabilities; supervised and unsupervised, deep learning and classical
- You will be responsible for the design & development of new APIs/microservices and deploy them using Python, Terraform and Kubernetes at scale
- You will use Workday’s vast computing resources on rich, exclusive datasets to deliver value that transforms the way our end-users experience WD
- Work with multi-functional teams to deliver scalable, secure and reliable solutions
- Building MLOps platform primarily using Kubeflow, and other ML ecosystem tools and services for a unified ML Development experience
- Effectively engage with data scientists, ML engineers, PMs and architects in requirements elaboration and drive technical solutions
- Own and develop cloud based services from end to end including infrastructure as code
- Design and build software solutions for efficient organization, storage and retrieval of data to enable substantial scale
- Understanding cloud computing and security to build robust cloud infrastructure and solutions for ML teams
- Build systems and dashboards to monitor service & ML health
- Lead in architecture reviews, code reviews and technology evaluation
- Research, evaluate, prototype and drive adoption of new ML tools with reliability and scale in mind
- Stay abreast of industry trends and emerging technologies, providing recommendations for continuous improvement of our DevOps and machine learning practices
- Design, implement, and maintain robust MLOps services for deploying, monitoring, and scaling machine learning development and data engineering primarily with Kubeflow
- Troubleshoot and resolve performance bottlenecks, system outages, and other operational issues in collaboration with the ML engineering teams
- Optimize public cloud-based infrastructure (AWS, GCP) to support the computational requirements of machine learning workloads
- Implement and manage CI/CD workflows to automate testing, integration, and delivery of machine learning components
- Ensure the security and compliance of machine learning platforms, implementing best practices for encryption, data protection and access controls
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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