Remote NLP Engineer | Transform Language with AI

Placements24; Mbombela (Nelspruit); Hybrid; ZAR 900,000 - 1,200,000; Full time

Job summary

Placements24 is seeking a remote-first NLP Engineer to design, develop, and deploy advanced NLP models. You will work on tasks including text summarization, sentiment analysis, and entity recognition within a flexible, remote environment, collaborating with an engineering team.

The role emphasizes deep learning with Python, Hugging Face, and Transformer architectures, enabling language understanding and generation across large text datasets.

Qualifications

• Master's or Ph.D. in Computer Science, Computational Linguistics, or a related field with NLP focus.
• 3+ years of NLP development experience.
• Strong Python skills and experience with NLP libraries (NLTK, spaCy, Hugging Face).
• Proficiency with deep learning frameworks (TensorFlow, PyTorch) for NLP.
• Experience with text preprocessing, feature extraction, and language modeling.
• Understanding of Transformers and large language models.

Responsibilities

• Develop and implement NLP models for tasks like text summarization, QA, topic modeling.
• Use ML/DL techniques for language understanding and generation.
• Process and analyze large volumes of unstructured text data.
• Collaborate with software engineers to integrate NLP into applications.
• Evaluate and refine NLP model performance for accuracy and relevance.
• Stay updated on NLP research and advancements.

Skills

NLP development

Python programming

Deep learning

Transformer models

Education

Master's or PhD in CS/Computational Linguistics

Tools

NLTK

spaCy

Hugging Face Transformers

TensorFlow

PyTorch

Job description

Placements24 is seeking a remote-first NLP Engineer to design, develop, and deploy advanced NLP models. You will work on tasks including text summarization, sentiment analysis, and entity recognition within a flexible, remote environment, collaborating with an engineering team.

The role emphasizes deep learning with Python, Hugging Face, and Transformer architectures, enabling language understanding and generation across large text datasets.