NLP & Natural LanguageProcessing Jobs
Build systems that understand and generate human language. Work on text classification, named entity recognition, sentiment analysis, machine translation, and conversational AI. $140k-$290k+ salaries.
NLP engineers build systems that process, understand, and generate human language. While the field has been transformed by large language models, there's still strong demand for specialists in areas like information extraction, text classification, multilingual NLP, speech recognition, and domain-specific language understanding.
NLP roles span from research positions at AI labs developing new language models to applied roles at companies building search engines, chatbots, content moderation systems, and document processing tools. Key skills include Python, PyTorch, HuggingFace Transformers, and deep understanding of language model architectures.
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Frequently Asked Questions
What's the difference between NLP and LLM engineering?
NLP is the broader field of building systems that understand and generate human language, encompassing everything from text classification to machine translation. LLM engineering is a specialization within NLP focused specifically on working with large language models -- fine-tuning, deployment, RAG systems, and evaluation. Many NLP engineers now work primarily with LLMs, but traditional NLP skills remain valuable for specialized tasks.
What skills are needed for NLP jobs?
Core skills include Python, PyTorch, and understanding of transformer architectures. Experience with HuggingFace Transformers, tokenization, embeddings, and text preprocessing is essential. For research roles, knowledge of attention mechanisms, pre-training objectives, and evaluation metrics is important. For applied roles, experience with APIs, model serving, and production systems is valued.