Senior ML Engineer — Document Intelligence Platform

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

Job summary

Workday in Pleasanton seeks a Machine Learning Engineer for the ML – Document Intelligence team to design and build the core Document Intelligence Platform as a Service, focusing on document entity extraction, entity resolution, and classification with cutting-edge AI/ML techniques.

You will collaborate with software engineers and product managers to deploy scalable ML pipelines, improve model performance, and drive end-to-end document processing workflows with a strong emphasis on

Qualifications

• Deep Technical ML Capability: 3+ years of experience researching, developing and deploying production-grade ML systems, including expertise in deep learning, NLP, Information Retrieval, and recommender systems using frameworks like PyTorch or TensorFlow.
• Generative AI & Agentic Systems: Proven track record of building and evaluating NLP and LLM-powered products, including expertise in RAG architectures, agentic frameworks (e.g., LangChain/LangGraph), and long-context LLM applications (e.g., Text-to-SQL).
• Engineering Excellence: 2+ years of Python experience with a focus on modular library design, asynchronous patterns, and scalable system architecture (state management/error handling) for non-deterministic AI outputs.

Responsibilities

• Design and implement LLM-based technologies for document parsing, entity extraction, and classification tasks.
• Apply traditional ML and deep learning techniques to enhance accuracy, efficiency, and scalability of document intelligence models.
• Build scalable ML pipelines and services for data preprocessing, training, and inference.
• Perform exploratory data analysis (EDA) on diverse document datasets to uncover insights and inform model development.
• Collaborate with software engineers, product managers, and other ML teams; write clean, maintainable code; participate in design reviews.

Skills

Python

NLP

Deep learning

PyTorch/TensorFlow

Information Retrieval

Recommender systems

Education

Advanced degree (Master’s or Ph.D.) in quantitative field

Tools

Docker/Kubernetes

AWS/GCP

PySpark

SQL

Job description

Workday in Pleasanton seeks a Machine Learning Engineer for the ML – Document Intelligence team to design and build the core Document Intelligence Platform as a Service, focusing on document entity extraction, entity resolution, and classification with cutting-edge AI/ML techniques.

You will collaborate with software engineers and product managers to deploy scalable ML pipelines, improve model performance, and drive end-to-end document processing workflows with a strong emphasis on