Manager of Machine Learning Engineering, Workday

• Bachelor's degree in Computer Science, Engineering, or a related technical field
• 8+ years of experience in production-level Software Development
• 3+ years of experience in a technical leadership or management role, leading software engineering teams
• 4+ years of experience in Python, with a consistent track record of shipping production code and systems
• 4+ years of experience building scalable data pipelines and working with large-scale datasets
• 4+ years of experience deploying production services to cloud platforms (e.g., AWS, GCP) and using containerization technologies (e.g., Docker, Kubernetes) for MLOps

Desirable

• As a Machine Learning Manager, you will lead a high-performing team of software and machine learning engineers focused on architecting, building, and deploying robust, scalable, and performant AI systems within Workday's product ecosystem
• You will be instrumental in guiding your team to transform ML solutions into production-ready systems, with a focus on building a platform for Workday developers and customers to build and deploy AI Agents, encompassing planning, reasoning, and action execution frameworks
• This role requires a unique blend of deep technical expertise in ML systems and a proven ability to lead, mentor, and develop engineering talent
• You will foster an environment of technical excellence, collaboration, and continuous improvement, ensuring your team delivers high-quality, impactful solutions that align with organizational goals
• Drive Agentic AI Platform Strategy & Vision: Guide the architectural design and implementation of scalable, performant Agentic AI platforms and advanced agentic capabilities such as tool calling, supervisor agents, multi-agent architectures, and human-in-the-loop integration. Define technical roadmaps and advocate for MLOps optimal standards
• Build and Operate Scalable ML Platforms: Oversee the design, implementation, and deployment of secure, scalable ML infrastructure, including Python web services and Kubernetes-based runtime architectures. Ensure seamless integration, leverage benchmark cloud deployment practices for robust platform support, and champion comprehensive logging, observability, metrics, and alerting for production systems
• Lead and Develop Your Team: Lead and mentor a high-performing team, fostering career growth, setting clear goals, providing feedback, and ensuring recognition. Cultivate productive connections and empower team members to grow their capabilities
• Drive Multi-functional Collaboration: Drive collaboration with various partners and customers to translate requirements into technical designs. Lead cooperative efforts across project teams, ensuring alignment and successful delivery of impactful solutions and platform support