We Love AI JobsNatural Language Processing (NLP)
The branch of AI focused on enabling computers to understand, interpret, and generate human language.
Natural language processing encompasses all AI techniques for working with human language — from basic text classification and named entity recognition to complex tasks like machine translation, summarization, and open-ended dialogue.
The field has been transformed by transformer-based models. Pre-LLM NLP involved feature engineering, word embeddings, and task-specific architectures. Modern NLP leverages large language models that can handle most language tasks through prompting alone, though specialized NLP pipelines remain important for production systems requiring precision and efficiency.
NLP engineers build text processing pipelines, design language understanding systems, and integrate LLMs into products. The role often requires expertise in linguistics, information retrieval, and evaluation methodology alongside core ML skills.
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Related Terms
Large Language Model (LLM)
A neural network trained on massive text datasets that can understand and generate human language.
Transformer
The neural network architecture behind modern LLMs, using self-attention mechanisms to process sequences in parallel.
Tokenization
The process of breaking text into smaller units (tokens) that language models can process.
Embeddings
Dense numerical representations of data (text, images, etc.) that capture semantic meaning in a format AI models can process.