Machine Learning Engineer (P3)

We're seeking a Machine Learning Engineer (P3) to join our Adoption Team, which develops intelligent agents and capabilities that enable customers to manage Workday efficiently and maximize their overall experience.

As a Machine Learning Engineer, you will apply your growing ML expertise to build and deploy ML components, develop your technical skills, and collaborate with core platform teams to integrate machine learning into Workday's administrative systems.

Key Responsibilities:

• 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.

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.

Salary: €72,000 EUR - €108,000 EUR

Work Environment: We offer a flexible work environment, with the expectation that employees spend at least half (50%) of their time each quarter in the office or in the field.