Machine Learning Engineer in Workday's AI Platform team developing systems for agent observability and optimization. Solving complex challenges with innovative ML solutions and advanced algorithms in a collaborative environment.
Responsibilities
Develop algorithms for automated node-level optimization within agent graphs
Architect Evaluation Pipelines using Kubeflow on the cloud
Build a Python-native framework for complex metrics
Implement real-time evaluation and A/B testing frameworks
Drive the design of metrics warehouse for actionable insights
Design, build, and deploy sophisticated AI agents
Own the entire ML lifecycle for high-quality, scalable deployment
Requirements
3+ years of professional experience as a Machine Learning Engineer
Demonstrated experience in building and evaluating AI agents
Expertise in prompt engineering and optimization
Proven understanding of statistical analysis and machine learning algorithms
Solid understanding of A/B testing and experimental design
Proficiency in modern ML frameworks (e.g. PyTorch, TensorFlow)
Expert-level Python skills
Experience with multi-threading and asynchronous call patterns
Experience designing 'Agent-in-the-loop' systems
Knowledge of MLOps and cloud services (e.g. AWS, GCP, Azure)
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