Principle Machine Learning Engineer

Job description

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 senior individual-contributor role as a Principal Machine Learning Engineer, you will bring deep applied ML expertise to a high-performing team of distributed-systems engineers, collaborating on technical strategy and automation across Workday's administration platform. Partnering with Engineering leadership and Product Managers, you will define technical strategy, architect and deploy production-grade ML infrastructure, and support fellow engineers while collaborating with core platform teams to seamlessly integrate machine learning into Workday's administrative systems. Drawing on your extensive industry background, you will work effectively within a collaborative ecosystem, transforming advanced technical capabilities into measurable business impact for Workday customers. Key ResponsibilitiesDesign, build, and productionize machine learning models and pipelines that integrate with Workday's platform-level systems. Set technical direction and 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. Lead and collaborate on 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 high-impact opportunities for ML-driven automation and intelligence. Mentor and provide technical guidance to other engineers on ML system design, coding practices, and architectural decisions. Evaluate and introduce new tools, frameworks, and techniques to keep the team's ML practices current and effective. Contribute to the long-term technical roadmap and architecture for ML capabilities within the Ampere team and the broader organization. Lead the architectural design and deployment of Generative AI capabilities and Large Language Model (LLM) applications About You Basic Qualifications 12+ years of professional experience in machine learning engineering, applied ML, or a closely related discipline, with a track record of shipping ML systems to production at scale. 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 self-directed at a principal level — shaping technical direction, partnering on architecture, and guiding projects from concept to delivery. Proven track record of designing, evaluation, and deploying Generative AI models and Large Language Models (LLMs) in enterprise production environments. Strong collaboration and communication skills, with experience mentoring engineers and influencing cross-functional stakeholders. Other Qualifications 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. 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. Primary Location Base Pay Range: €116,000 EUR - €174,000 EUR Ireland 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 accommodations@workday.com, as far in advance as possible. Are you being referred to one of our roles? If so, ask your connection at Workday about o