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About The Team
About The Role Machine Learning Engineer Document Intelligence Platform as a Service
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Support the design and implementation of LLM-based technologies for document parsing, entity extraction, and classification tasks.
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Apply traditional ML and deep learning techniques to continuously enhance the accuracy, efficiency, and scalability of our document intelligence models.
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Build scalable ML pipelines and services for data preprocessing, feature engineering, training, and inference, enabling high-volume document processing workflows.
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Perform exploratory data analysis (EDA) on diverse document datasets to uncover valuable insights, optimize feature engineering, and inform model development.
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Collaborate with software engineers, Workday app developers, product managers, and other ML teams
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Take ownership for finding creative solutions that move projects forward
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Write clean, maintainable, and testable code following best practices in software engineering, including automation, observability, and scalability.
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Conduct code reviews, participate in design discussions, and engage in collaborative team activities like hackathons and knowledge-sharing sessions.
About You Basic Qualifications
- 4+ yrs experience as part of a data science, machine learning software development team or relevant work in a PhD program.
- 3+ years of experience with Python and ML frameworks such as PyTorch or TensorFlow
- 2+ years experience related to machine learning, deep learning, NLP, GenAI, multi-agent AI systems, distributed training, model hosting, etc.
- 3+ years experience in handling large-scale, complex data sets, data modeling, and productizing machine learning algorithms.
Other Qualifications
- Strong knowledge of both classical machine learning and deep learning
- Working knowledge of LLMs and their use in building agentic systems
- Proficiency with using Spark for large-scale data processing
- Excellent communication and collaboration skills, with a strong focus on team success and customer impact.
Posting End Date: 05/05/2025 If hired in Colorado click here for information about Workday's comprehensive benefits in Colorado
The application deadline for this role is the same as the posting end date stated. Workday Pay Transparency Statement
Our Approach to Flexible Work spend at least half (50%) of our time each quarter in the office or in the field
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