Staff Software Engineer - NLP
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17 open NLP engineer jobs at 11 employers, updated twice a day.
In the week to 27 September, 17 NLP engineer roles were open at 11 employers. 4 new roles were posted during the week. The countries with the most are the United States, the United Kingdom and India. Of the roles that say how they work, 0% are remote or hybrid.
Among the roles listed here, NLP engineers are concentrated in the United States, which accounts for nearly half of all postings, with India representing roughly a quarter and smaller shares in China, Poland and Germany. The field skews toward experience: senior roles make up the largest single seniority group, while mid-level, lead, intern and manager postings are each present in roughly equal and smaller shares. About half of all roles sit with a relatively small number of employers, suggesting some consolidation among active hirers. A notable portion of postings are older than a month, though a meaningful share arrived in the past two weeks. LLMs, Python and general NLP appear in the great majority of descriptions, pointing to where employer attention is focused right now.
Figures are measured every Monday.
NLP engineers build and maintain systems that process, understand or generate human language. The role sits at the intersection of machine learning engineering and linguistic modelling, and differs from a general machine learning engineer by its focus on text, speech and related modalities. Core tools include deep learning frameworks and the pretrained model ecosystems built around transformer architectures; the Hugging Face Transformers library is a widely used open-source resource that provides pretrained models, inference pipelines and training utilities. People enter the field from computer science, linguistics or related backgrounds, often through research or applied project work, and progress toward senior or lead roles as they deepen expertise in model evaluation, fine-tuning and production deployment.
Descriptions mention LLMs in the great majority of postings, and Python almost as often, so strong Python fluency and hands-on experience with large language models are clearly central. PyTorch appears in a large minority of descriptions alongside APIs, suggesting comfort with both model-level work and service integration. Evaluation, RAG, fine-tuning and transformers each appear in roughly a quarter to a third of postings, pointing to a candidate who can adapt and assess models rather than only apply them out of the box.
Share of the open roles' descriptions that mention it, from a sample of 17. A mention is not a requirement.
On-site work dominates strongly among roles that state a work mode, with the great majority of postings expecting physical attendance. Hybrid and fully remote arrangements each account for a small minority of those stating a preference. Candidates open only to remote work will find the pool here notably narrower than for some other engineering disciplines.
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