Software Engineer

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 Adoption Team develops intelligent agents and capabilities that enable customers to manage Workday efficiently and maximize their overall experience. As a distributed-systems focused engineering group, we build and scale the agentic administrative tooling which supports Workday's core product suite.

About the Role

In this individual-contributor role as a Machine Learning Engineer (P3), you will apply your growing ML expertise alongside a team of distributed-systems engineers, contributing to automation and intelligence initiatives across Workday's administration platform. Working under the guidance of senior engineers, Engineering leads, and Product Managers, you will help build and deploy ML components, develop your technical skills, and collaborate with core platform teams to integrate machine learning into Workday's administrative systems.

You will work within a collaborative ecosystem, helping translate technical work into measurable value for Workday customers while growing your expertise in applied ML engineering.

Key Responsibilities

• Ability to work individually and as part of a team to build and help productionize machine learning models and pipelines that integrate with Workday's platform-level systems.
• Follow and help apply established best practices for ML engineering, including model development, evaluation, deployment, and monitoring.
• Work with distributed-systems engineers to help ensure ML solutions scale reliably across Workday's multi-tenant architecture.
• Contribute to components of the ML lifecycle - including data preparation, model training, deployment support, and monitoring in production.
• Collaborate with product management, data engineering, and platform teams on well-scoped ML-driven automation initiatives.
• Participate in code reviews and knowledge-sharing sessions to build technical skills and support team quality standards.
• Stay current with new tools, frameworks, and techniques relevant to the team's ML practices.
• Support the team's technical roadmap for ML capabilities within the Adoption team.
• Develop and deploy Generative AI capabilities and Large Language Model (LLM) applications

About You

Basic Qualifications

• 4+ years of experience in machine learning engineering, applied ML, or a closely related discipline, including exposure to deploying ML models to production.
• Solid software engineering fundamentals, with some experience in distributed or production systems.
• Familiarity with common ML frameworks and languages (e.g., Python, PyTorch/TensorFlow) and basic MLOps practices (model versioning, monitoring).
• Ability to execute well-defined technical tasks with increasing independence, escalating and collaborating with senior engineers as needed.
• Good collaboration and communication skills, with willingness to learn from and work closely with more senior engineers.

Other Qualifications

• Exposure to large-scale, multi-tenant SaaS platforms.
• Interest or coursework/project experience in applying ML to enterprise/administrative platform problems (e.g., anomaly detection, automation, intelligent configuration).
• Familiarity with cloud infrastructure and data processing systems.
• Practical experience developing generative AI capabilities and integrating LLMs, with a preference for orchestration frameworks such as LangChain and agentic architectures.
• Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, or equivalent practical experience.

Workday Pay Transparency Statement (For EU Locations Only)

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.

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.

Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process!

At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers.

Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not.

In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.