Remote NLP Engineer: Text Analytics & AI Pipelines

Bright Vision Technologies; Irving (TX); Remote; USD 115,000 - 165,000; Full time

Job summary

Bright Vision Technologies is seeking a Natural Language Processing Engineer to develop language-processing solutions for extracting, classifying, searching, and interpreting text. The role will prepare text datasets, build and evaluate NLP models, develop production inference services, and collaborate with application and data teams to integrate language intelligence into enterprise workflows.

Key responsibilities include developing NLP pipelines for classification, entity extraction, semantic

Qualifications

• 5+ years in NLP, ML, or applied language technology
• Strong Python and NLP library experience (spaCy, NLTK, Transformers)
• Knowledge of tokenization, embeddings, language representations, text classification, and information extraction
• Experience preparing text datasets and evaluating models using precision, recall, F1, or ranking metrics
• Experience building APIs, batch workflows, or other production model inference systems
• Experience with ML fundamentals and PyTorch or TensorFlow

Responsibilities

• Develop NLP pipelines for text classification, entity extraction, semantic search, summarization, or language understanding
• Prepare and label text datasets, normalize content, and implement preprocessing and feature strategies
• Train, fine-tune, or adapt language models and evaluate results with task-specific metrics
• Build inference APIs or batch processing components and integrate them with enterprise applications
• Monitor model quality, analyze errors, and document performance and improvement opportunities

Skills

Python programming

NLP libraries

Tokenization & embeddings

Model training & evaluation

API development

Production ML / inference

Tools

PyTorch

TensorFlow

Hugging Face Transformers

Job description

Bright Vision Technologies is seeking a Natural Language Processing Engineer to develop language-processing solutions for extracting, classifying, searching, and interpreting text. The role will prepare text datasets, build and evaluate NLP models, develop production inference services, and collaborate with application and data teams to integrate language intelligence into enterprise workflows.

Key responsibilities include developing NLP pipelines for classification, entity extraction, semantic