Remote NLP Engineer

Placements24; Polokwane; Hybrid; ZAR 600,000 - 900,000; Full time

Benefits offered by this job

Competitive salary

Remote benefits package

Flexible work hours

Advanced computational resources

Job summary

Placements24 is seeking a highly skilled Remote NLP Engineer to join its innovative and fully remote team. You will design, train, and deploy NLP models, work with large text datasets, and collaborate with data scientists to integrate models into production systems.

The role emphasizes deep learning techniques, cloud and containerization expertise, and the ability to work independently in a remote setting from anywhere. Competitive salary and remote benefits are included.

Qualifications

• Master's or Ph.D. in Computer Science, Computational Linguistics, or a related field.
• 3+ years of professional experience in Natural Language Processing.
• Strong programming skills in Python and experience with NLP libraries (e.g., NLTK, spaCy, Hugging Face Transformers).
• Solid understanding of machine learning and deep learning techniques applied to NLP.
• Experience with cloud platforms and containerization (e.g., Docker, Kubernetes).
• Excellent problem-solving skills and the ability to work independently in a remote setting.

Responsibilities

• Design, train, and evaluate NLP models for tasks such as text classification, named entity recognition, sentiment analysis, and machine translation.
• Develop and implement efficient pipelines for processing and analyzing large volumes of text data.
• Collaborate with data scientists and software engineers to integrate NLP models into production systems.
• Research and apply state-of-the-art NLP techniques, including deep learning models like Transformers.
• Optimize NLP models for performance, accuracy, and scalability.
• Contribute to the development of robust and scalable NLP infrastructure.

Skills

Python

NLP libraries

Machine Learning

Cloud platforms

Docker

Kubernetes

Remote work

Education

Master's or PhD in CS/CL or related

Tools

NLTK

spaCy

Hugging Face Transformers

Job description

Our client is seeking a highly skilled Remote NLP Engineer to join their innovative and fully remote team. This position focuses on developing and deploying state-of-the-art Natural Language Processing models and applications. You will work with large text datasets, design sophisticated algorithms, and contribute to products that understand and process human language. This is an exceptional opportunity for an NLP expert looking to work flexibly from anywhere while pushing the boundaries of language technology.

Key Responsibilities

• Design, train, and evaluate NLP models for tasks such as text classification, named entity recognition, sentiment analysis, and machine translation.
• Develop and implement efficient pipelines for processing and analyzing large volumes of text data.
• Collaborate with data scientists and software engineers to integrate NLP models into production systems.
• Research and apply state-of-the-art NLP techniques, including deep learning models like Transformers.
• Optimize NLP models for performance, accuracy, and scalability.
• Contribute to the development of robust and scalable NLP infrastructure.

Requirements

• Master's or Ph.D. in Computer Science, Computational Linguistics, or a related field.
• 3+ years of professional experience in Natural Language Processing.
• Strong programming skills in Python and experience with NLP libraries (e.g., NLTK, spaCy, Hugging Face Transformers).
• Solid understanding of machine learning and deep learning techniques applied to NLP.
• Experience with cloud platforms and containerization (e.g., Docker, Kubernetes).
• Excellent problem-solving skills and the ability to work independently in a remote setting.

Benefits

• Competitive salary and comprehensive remote benefits package.
• Flexible work hours and the ability to work from anywhere.
• Opportunity to work on challenging and impactful NLP projects.
• Access to advanced computational resources.
• A collaborative and forward-thinking remote team environment.