NLP Data Engineering Intern at iManage in Chicago, IL

Summary: iManage is dedicated to Making Knowledge WorkTM, providing a dynamic internship program for students. As an NLP Data Engineering Intern, you will gain hands-on experience in designing and optimizing text data pipelines to support AI and machine learning solutions, collaborating with various teams to enhance document data for intelligent features across the platform. Responsibilities: - Performing exploratory analyses on large text corpora and developing preprocessing pipelines for training and evaluation data - Supporting the design of automated workflows for text normalization, deduplication, language identification, PII redaction, and metadata enrichment - Assisting with building automated data validation processes to ensure accuracy and consistency of NLP datasets - Contributing to dataset curation, prompt dataset preparation, labeling coordination, and text quality validation to support model fine-tuning, semantic search, and Gen AI evaluations - Partnering with the Applied AI team to understand data requirements and help build data interfaces for machine learning systems - Learning and applying data lineage best practices and data privacy, security, and governance principles - Maintaining highest quality standards through processes that identify and correct mistakes and inconsistencies Required Qualifications: - Current enrollment in a Master's, or PhD program in Computer Science, Data Engineering, Data Science, Applied Mathematics, Computational Linguistics, or a related quantitative field - Proficiency in Python and experience using it to extract, structure, classify, and analyze text data - Foundational understanding of NLP concepts such as tokenization, embeddings, and semantic search - Familiarity with standard NLP libraries such as SpaCy, HuggingFace Datasets, or NLTK - Solid knowledge of data structures, algorithms, and statistics - Proficiency with Git and collaborative development workflows - A passion to learn and improve, and an eagerness to share knowledge with colleagues - Problem-solving, creativity, curiosity, and a collaborative mindset Preferred Qualifications: - Exposure to Microsoft Azure services such as Fabric, ADLS, AI Foundry, or Azure ML - Experience with data pipeline orchestration or workflow automation tools like Databricks - Familiarity with knowledge graphs or semantic data modeling Required Skills: Python, Natural Language Processing, Tokenization, Embeddings, Semantic search, SpaCy, HuggingFace Datasets, NLTK, Data structures, Algorithms, Statistics, Git, Curiosity, Collaborative mindset