Sr ML Software Development Engineer, Admin

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.

Admin Central is building the future of how administrators work across Workday, turning a fragmented patchwork of tools and disconnected AI into a single, unified experience. Within Admin Central, Workday implementations move from being driven by human effort to being powered by intelligence designed into the platform.

As a Sr Software Development Engineer (ML/AI) on the Admin Central team, you will lead the technical design, development, and scaling of advanced ML pipelines, predictive analytics engines, and AI-driven recommendation features. Admin Central sits at the core of Workday's enterprise AI and automation strategy, serving over 700 customer accounts to handle ad hoc and ambient agentic requests through high-throughput analytics and agentic workflows.

In this role, you will bridge the gap between production-grade distributed software engineering and modern ML/LLM architectures. You will architect low-latency inference services, build automated feature stores and retraining pipelines over big data infrastructure (Kafka, Spark/Flink, Click House, S3), and extend AI observability across agent execution loops using frameworks like Lang Smith and Lang Chain.

• ML Infrastructure & Pipeline Engineering:
  Architect, deploy, and maintain end-to-end Machine Learning pipelines—from distributed data ingestion and feature engineering to model training, evaluation, and production deployment.
• Agentic AI & Recommendation Engines:
  Design algorithms and LLM-driven recommendation features (e.g., IDD insights, next-best-action models) that optimize agentic workflows and tool usage.
• Low-Latency Inference & Scaling:
  Optimize real-time model inference and scoring microservices to ensure sub-second response times across high-concurrency multi-tenant environments.
• LLM & Agentic Observability:
  Integrate telemetry and tracing (Open Telemetry, Lang Chain, Lang Smith) into ML pipelines to track model performance, prompt/response drift, and execution efficiency.
• Data & Feature Store Architecture:
  Collaborate with core backend engineers to leverage big data platforms (Click House, Apache Iceberg, Spark) for high-dimensional feature retrieval and analytics.
• Cross-Functional Leadership:
  Partner closely with Product Managers, Data Engineering, SRE, and Legal/Compliance to translate complex business and governance requirements into scalable ML solutions.

• 8+ years in ML research, development, and implementation of advanced models/techniques, including 4+ years building, deploying, and operating production ML…