Senior Machine Learning Engineer

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.

In this senior individual-contributor role as a Senior Machine Learning Engineer, you will bring strong applied ML expertise to a high-performing team of distributed-systems engineers, contributing to technical strategy and automation across Workday's administration platform. Working closely with Engineering leads and Product Managers, you will help shape technical approach, build and deploy production-grade ML systems, and support fellow engineers while partnering with core platform teams to integrate machine learning into Workday's administrative systems.

Drawing on your solid industry background, you will work effectively within a collaborative ecosystem, turning technical capabilities into measurable business impact for Workday customers.

• →Design, build, and productionize machine learning models and pipelines that integrate with Workday's platform-level systems.
• →Apply and help refine best practices for ML engineering within the team, including model development, evaluation, deployment, and monitoring.
• →Partner with distributed-systems engineers to ensure ML solutions scale reliably across Workday's multi-tenant architecture.
• →Own significant pieces of end-to-end ML lifecycle work — from problem framing and data strategy through model training, deployment, and performance monitoring in production.
• →Collaborate cross-functionally with product management, data engineering, and platform teams to identify opportunities for ML-driven automation and intelligence.
• →Provide technical guidance and code/design review to other engineers on ML system design and implementation.
• →Evaluate new tools, frameworks, and techniques to help keep the team's ML practices current and effective.
• →Contribute to the technical roadmap for ML capabilities within the Adoption team.
• →Design and deploy Generative AI capabilities and Large Language Model (LLM) applications

• Substantial professional experience in machine learning engineering, applied ML, or a closely related discipline, with a track record of shipping ML systems to production.
• Strong software engineering fundamentals, including experience building and operating distributed, production-grade systems.
• Proficiency with common ML frameworks and languages (e.g., Python, PyTorch/TensorFlow) and with MLOps practices (model versioning, CI/CD for ML, monitoring).
• Ability to work with a good degree of independence — contributing to technical direction, participating in architecture discussions, and driving projects from concept to delivery.
• Demonstrated technical leadership and collaboration skills through experience with cross-team initiatives, establishing technical standards, and mentoring junior and mid-level engineers.
• Demonstrated experience designing and developing with Generative AI technologies and LLM integration in production systems.

• 7+ years of experience working within large-scale, multi-tenant SaaS platforms.
• Background in applying ML to enterprise/administrative platform problems (e.g., anomaly detection, automation, intelligent configuration).
• Hands-on familiarity with LLM orchestration frameworks (preferably LangChain) and AI agentic architectures.
• Experience with cloud infrastructure and large-scale data processing systems.
• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or a related field, or equivalent practical experience.

Listed below is the base salary range applicable to this position. Workday pay ranges (and the precise pay offered to the successful candidate) are based on a number of objective criteria such as relevant experience and skills, and educational qualifications, level of responsibility, demands of the role, work location and business need. 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 awarded by Workday Inc. For more information regarding Workday’s comprehensive benefits, please click here.

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