Principal Software Engineer developing machine learning features for Workday's HR & Talent platform. Collaborating with engineers to deliver infrastructure and APIs for ML capabilities at scale.
Responsibilities
Lead the design and implementation of high-throughput microservices and APIs (Python/Go) that serve as the backbone for Workday’s ML ecosystem
Build and optimize a unified ML development experience using Kubeflow, Kubernetes (EKS/GKE), and specialized compute orchestration (CPUs/GPUs)
Own the end-to-end lifecycle of cloud-based services, utilizing Infrastructure as Code (Terraform) to build resilient, self-healing environments
Lead architecture reviews, code reviews, and technology evaluations to ensure our systems meet 99.99% reliability standards
Design the architectural patterns and observability frameworks required to support emerging Agentic AI systems and LLM-based applications
Partner with data scientists, ML engineers, and architects to translate complex data needs into elegant, maintainable software solutions
Research and drive adoption of new infrastructure tools with a focus on reliability, security, and enterprise-grade scale
Requirements
6 or more years of validated industry experience
Bachelor’s and/or Master’s degree in Computer Science or Computer Engineering
Strong software engineering experience with designing and building scalable, distributed systems
Deep understanding of cloud computing, cloud infrastructure, and distributed systems; experience with AWS and GCP
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