About the Role

Workday is seeking ML Engineers to join the AI Platform team, focusing on Agent Optimization & Evaluation and Information Retrieval. You will architect agentic AI systems, advance information retrieval, and scale evaluation pipelines. This role bridges research and production, leveraging exclusive enterprise datasets to impact over 31 million users.

Responsibilities

Architect Agentic AI: Design and deploy reasoning, planning, and swarm agents. Drive Meta-ML & Optimization: Develop algorithms for automated node-level optimization within agent graphs. Advance Information Retrieval: Build hybrid, agentic search systems and semantic parsing products (Text-to-SQL/Python). Scale Evaluation & Observability: Engineer cloud-based pipelines and A/B testing frameworks. Lead the ML Lifecycle: Own end-to-end MLOps from exploration to production. Define Strategic Roadmaps: Identify ML opportunities and propose solutions to leadership. Collaborate with Autonomy: Work cross-functionally with PMs and Engineers.

Requirements

3+ years (MLE III) or 6+ years (Senior MLE) of experience developing and deploying production-grade ML systems. Expertise in deep learning, NLP, Information Retrieval, and recommender systems using PyTorch or TensorFlow. Proven track record with NLP/LLM products including RAG architectures, agentic frameworks (LangChain/LangGraph), and long-context LLM applications. Expert-level Python experience with modular library design, asynchronous patterns, and scalable system architecture.

Workday

Copenhagen · DK

Senior Machine Learning Engineer (LLMs, MLOps, Computer Vision & Cloud AI)

Dutech Systems

AUSTIN · US

Machine Learning Engineer III / Senior Machine Learning Engineer - AI Platform

About the Role

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Requirements

Workday

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