Senior ML Engineer, Document Intelligence - Hybrid

Workday; Pleasanton (CA); Hybrid; USD 160,000 - 240,000; Full time

Job summary

Workday is seeking a Machine Learning Engineer to join the ML - Document Intelligence team to drive the design and development of the core Document Intelligence Platform as a Service. You will work on building and optimizing features like document entity extraction, entity resolution and classification, leveraging cutting-edge AI/ML techniques.

Your focus includes designing LLM-based document parsing, improving model accuracy and building scalable pipelines for data preprocessing, training and

Qualifications

• 3+ years of experience researching, developing and deploying production-grade ML systems, including deep learning, NLP, information retrieval, and recommender systems using PyTorch or TensorFlow.
• Proven track record of building NLP/LLM-powered products, including RAG architectures and LangChain/LangGraph.
• 2+ years Python experience with modular design, asynchronous patterns, and scalable system architecture.

Responsibilities

• Design and implement LLM-based document parsing, entity extraction, and classification tasks.
• Improve accuracy, efficiency and scalability of document intelligence models using traditional ML and deep learning.
• Build scalable ML pipelines for preprocessing, training and inference for high-volume document processing.
• Collaborate with software engineers, product managers and other ML teams; perform code reviews.

Job description

Workday is seeking a Machine Learning Engineer to join the ML - Document Intelligence team to drive the design and development of the core Document Intelligence Platform as a Service. You will work on building and optimizing features like document entity extraction, entity resolution and classification, leveraging cutting-edge AI/ML techniques.

Your focus includes designing LLM-based document parsing, improving model accuracy and building scalable pipelines for data preprocessing, training and