1 day ago
Base Salary
$136k - $240k/yr
Responsibilities
- Design and implement LLM-based technologies for document parsing, entity extraction, and classification.
- Apply traditional machine learning and deep learning techniques to improve model accuracy, efficiency, and scalability.
- Build scalable ML pipelines and services for data preprocessing, feature engineering, training, and inference.
- Perform exploratory data analysis on document datasets to guide feature engineering and model development.
- Develop generic document entity extraction, entity resolution, and document classification capabilities.
- Write clean, maintainable, modular, testable code with automation, observability, and scalability.
- Conduct code reviews, participate in design discussions, and contribute to hackathons and knowledge-sharing sessions.
- Collaborate with software engineers, Workday application developers, product managers, and other ML teams.
- Lead cross-functional teams, mentor junior engineers, and independently solve ambiguous problems.
Requirements
- At least 3 years of experience researching, developing, and deploying production-grade ML systems.
- Expertise in deep learning, NLP, information retrieval, and recommender systems using frameworks such as PyTorch or TensorFlow.
- Experience building and evaluating NLP and LLM-powered products, including RAG architectures, agentic frameworks such as LangChain or LangGraph, and long-context LLM applications such as Text-to-SQL.
- At least 2 years of Python experience focused on modular library design, asynchronous patterns, and scalable system architecture.
- A master’s or Ph.D. in a quantitative field, or a strong portfolio of peer-reviewed research publications.
- Proficiency in DSPy, reinforcement learning, imitation learning, graph neural networks, multimodal models, PySpark, and SQL.
- Experience with A/B testing, knowledge graphs, and curation of golden datasets for model benchmarking.
- Hands-on experience with the full ML lifecycle, including PEFT model fine-tuning, evaluation frameworks such as DeepEval or RAGAS, and cloud-native deployment with Docker, Kubernetes, AWS, or GCP.
- Demonstrated ability to lead cross-functional teams, mentor junior engineers, and work autonomously on ambiguous problems.
Benefits
- Flexible work arrangement requiring at least 50% of each quarter in the office or field, with remote home-office options.
- Role may be eligible for the Workday Bonus Plan or a role-specific commission/bonus and annual refresh stock grants.
- Workday provides comprehensive benefits and reasonable accommodations.
Tech Stack
Categories
About Workday
Workday builds cloud-based enterprise applications for human capital management and financial management, including payroll, time tracking, expenses, planning, and procurement, sold on a subscription basis with professional services. Founded in 2005 and headquartered in Pleasanton, California, it is a public company traded on NASDAQ as WDAY. Organizations worldwide use Workday to unify HR and finance data, automate processes, and apply AI to workforce and financial operations.