Sr. Analytics Engineer AI-ML

Your work days are brighter here.

At Workday, it all began with a conversation over breakfast. When our founders met at a sunny California diner, they came up with an idea to revolutionize the enterprise software market. And when we began to rise, one thing that really set us apart was our culture. A culture which was driven by our value of putting our people first. And ever since, the happiness, development, and contribution of every Workmate is central to who we are. Our Workmates believe a healthy employee-centric, collaborative culture is the essential mix of ingredients for success in business. That’s why we look after our people, communities and the planet while still being profitable. Feel encouraged to shine, however that manifests: you don’t need to hide who you are. You can feel the energy and the passion, it's what makes us unique. Inspired to make a brighter work day for all and transform with us to the next stage of our growth journey? Bring your brightest version of you and have a brighter work day here.

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About the Team

The Data Platform and Observability Engineering team, located in Pleasanton, CA; Boston, MA; Atlanta, GA and Dublin, Ireland, is vital to enabling real-time insights across Workday's platforms, infrastructure, and applications. We're committed to developing large-scale distributed data systems that support crucial Workday applications.
Our team provides software for the collection, ingestion, storage, analytics, and visualization of critical data assets. We lead hundreds of terabytes of data, encapsulating billions of messages produced daily by Workday applications and services.
We are looking for an Analytics AI/ML Engineer who combines deep technical expertise in machine learning with strong engineering fundamentals. This engineer will play a crucial role in building and deploying AI/ML solutions that transform our operational data into intelligent insights. If you have a passion for developing production-ready ML systems and the technical skills to build scalable AI solutions from the ground up, we would love to hear from you.

About the Role

• Design and implement machine learning models for anomaly detection, predictive analytics, and root cause analysis to support faster insights for Workday's systems observability

• Develop correlation engines using complex ML algorithms to identify patterns and relationships in sophisticated multi-dimensional datasets

• Create and optimize feature engineering pipelines that transform raw observability data into actionable ML features

• Implement and deploy ML models for service outage prediction, performance optimization

• Connecting data to the actionable model output that will help with reducing our MTTD/MTTR

• Build intelligent agentic systems that can autonomously monitor, diagnose, and recommend remediation actions for system health and performance issues

• Design and implement LLM-powered solutions for automated log analysis, incident analysis, and natural language querying of observability data

• Collaborate with data engineers to design ML-optimized data schemas and storage solutions

• Develop real-time inference systems that can process high-velocity streaming data with low latency

• Research and prototype next-generation AI techniques including deep learning, time series forecasting, and unsupervised learning methods

• Work closely with analytics leaders and product teams to translate business requirements into technical ML solutions

• Contribute to the development of internal ML platforms and tools that enable self-service AI capabilities

About You

Basic Qualifications

• 3+ years of hands-on experience building and deploying machine learning models in production environments

• 5+ years of software engineering experience with focus on data-intensive applications

• Bachelor's degree in Computer Science, Machine Learning, Data Science, or equival