Jobs / United States / Workday INC
Machine Learning Engineer - Payroll
Workday INC · 🇺🇸 USA, CA, Pleasanton
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 255 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 103 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Workday INC paid sponsored hires in similar roles3 certified filings for “Principal, Machine Learning Engineer” (Software Developers) in OR: $128k–$205k, median $129k. Most were filed at wage level II (67%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
Or apply yourself on the official page →
Sponsor Radar — Workday INC
The US Department of Labor certified 255 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 103 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Workday INC →
About the role
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 co