Remote NLP Engineer for Generative AI & LLMs

Placements24; East London; Hybrid; ZAR 900,000 - 1,300,000; Full time

Benefits offered by this job

Remote work

Health, dental, and vision insurance

Professional development

Job summary

Placements24 is seeking a talented NLP Engineer to join a fully remote team advancing generative AI and NLP models. The role focuses on developing, training, and refining large language models, with emphasis on text generation, dialogue systems, and data-driven insights.

Strong background in NLP and deep learning is essential. You will work with state-of-the-art tools (Transformers, PyTorch, TensorFlow) and cloud platforms, collaborating with researchers to deploy models into production in a

Qualifications

• Master’s or Ph.D. in Computer Science, Computational Linguistics, AI, or related field.
• Proven experience in Natural Language Processing (NLP) and machine learning.
• Hands-on experience with large language models (LLMs) and generative AI techniques.

Responsibilities

• Develop, train, and fine-tune LLMs and other generative AI models for NLP tasks.
• Implement and optimize NLP algorithms for text generation, summarization, translation, and chatbots.
• Collaborate with researchers and engineers to integrate NLP models into production systems.
• Process and analyze large text datasets, ensuring data quality for training.
• Evaluate model performance and implement enhancements.

Skills

NLP

Machine Learning

Python

Deep Learning

LLMs

Education

Master's or Ph.D. in Computer Science, Computational Linguistics, AI, or related field

Tools

Hugging Face Transformers

NLTK

spaCy

TensorFlow

PyTorch

Job description

Placements24 is seeking a talented NLP Engineer to join a fully remote team advancing generative AI and NLP models. The role focuses on developing, training, and refining large language models, with emphasis on text generation, dialogue systems, and data-driven insights.

Strong background in NLP and deep learning is essential. You will work with state-of-the-art tools (Transformers, PyTorch, TensorFlow) and cloud platforms, collaborating with researchers to deploy models into production in a