À propos de ce poste Machine Learning Engineer - Payroll chez Workday
Your work days are brighter here.
We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too.
About the Team
The Payroll AI and Data team is helping transform how payroll is processed for Workday customers around the world. Payroll touches nearly everyone who works, and the data behind it is complex, time-sensitive, and deeply important. Our work helps customers process payroll more accurately, efficiently, and confidently, so employees can be paid correctly and on time.We work with large-scale HR and Payroll datasets to build data and AI-driven solutions that improve the payroll experience for administrators and employees. In the year ahead, the team will focus on applying modern machine learning, generative AI, and AI agent technologies to deliver predictive analytics, recommendations, and automation that make payroll processing simpler and more effective.
This is a team for people who enjoy solving meaningful problems with data. We value curiosity, thoughtful collaboration, and practical innovation. You will work with people who care about building trustworthy AI solutions that create real value for Workday customers and support Workday’s mission to make work better.
About the Role
As a Machine Learning Engineer, you will help design, develop, and deliver AI and machine learning solutions that support payroll products at global scale. You will work with product managers, software engineers, data scientists, and other partners to understand customer needs and turn rich HR and Payroll data into useful product experiences.
You will use Workday’s AI development environment and tools to explore data, build models, evaluate performance, and help bring machine learning capabilities into production. Your work will support predictive analytics, intelligent recommendations, and automated experiences that help payroll administrators work more efficiently and help users have a better payroll processing experience.
In this role, you will:
Develop data and AI-driven solutions for enterprise payroll products serving organizations of many sizes and industries.
Explore, prepare, and transform large-scale HR and Payroll datasets for machine learning use cases.
Design, build, evaluate, and improve machine learning models, prompts, and frameworks.
Partner with product managers, software engineers, and data scientists to bring applied machine learning capabilities from concept through production.
Apply modern machine learning, deep learning, natural language processing, generative AI, and AI agent approaches to payroll challenges.
Contribute to model development practices that support scalability, reliability, quality, and responsible use of AI.
Learn payroll domain concepts and use that context to build solutions that are practical, trusted, and valuable for customers.
About You
Basic Qualifications
5+ years of experience as part of a data science, machine learning, or software development team.
3+ years of experience using Python and machine learning frameworks such as PyTorch, TensorFlow, or similar tools.
3+ years of experience working with large-scale datasets, including data modeling, feature development, or data transformation.
3+ years of experience building, evaluating, or productizing machine learning models or algorithms.
Other Qualifications
Experience with machine learning, including selecting appropriate approaches, preparing data, training models, evaluating results, and applying models to practical product problems.
Experience with model building, including feature engineering, experimentation, performance analysis, and iteration based on data and user needs.
Experience with model development practices, including model evaluation, deployment considerations, monitoring, and improvement over time.
Familiarity with model-based design concepts, including using models to represent complex systems, test assumptions, and guide solution design.
Experience with deep learning, natural language processing, generative AI, distributed training, model hosting, or multi-agent AI systems.
Experience bringing applied machine learning products from design through production.
Ability to work collaboratively with product managers, software engineers, and data scientists to deliver customer-focused AI solutions.
Clear communication skills, including the ability to explain technical concepts and model behavior to technical and non-technical partners.
Interest in learning HR and Payroll data, processes, and customer needs.
Advanced degree in Computer Science, Mathematics, Engineering, or a related field is a plus.
Workday Pay Transparency Statement
The annualized base salary ranges for the primary location and any additional locations are listed below. Workday pay ranges vary based on work location. As a part of the total compensation package, this role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus, as well as annual refresh stock grants. Recruiters can share more detail during the hiring process. Each candidate’s compensation offer will be based on multiple factors including, but not limited to, geography, experience, skills, job duties, and business need, among other things. For more information regarding Workday’s comprehensive benefits, please click here.
Primary Location: USA.CA.Pleasanton
Our Approach to Flexible Work
With Flex Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role). This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Those in our remote "home office" roles also have the opportunity to come together in our offices for important moments that matter.
Pursuant to applicable Fair Chance law, Workday will consider for employment qualified applicants with arrest and conviction records.
Workday is an Equal Opportunity Employer including individuals with disabilities and protected veterans.
Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law.
Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law.
If you require a reasonable accommodation, you may email [email protected], as far in advance as possible.
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