NLP Developer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an NLP Developer on a remote contract, focusing on developing and deploying healthcare-specific NLP models. Key skills include expertise in BERT and cloud platforms (AWS/Azure/GCP), along with knowledge of medical terminologies and MLOps practices.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
August 8, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Remote
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Datasets #"ETL (Extract #Transform #Load)" #Model Deployment #AWS (Amazon Web Services) #Deployment #NLP (Natural Language Processing) #GCP (Google Cloud Platform) #Data Science #Scala #Cloud #BERT #Azure
Role description
Role: NLP Developer or Engineer
Location: Remote
Contract position.
Job Description:
• Develop and deploy NLP models to process unstructured medical documents and clinical text.
• Fine-tune and optimize transformer models (BERT, BioBERT, ClinicalBERT) for healthcare-specific applications.
• Build scalable and efficient NLP pipelines for document processing and information extraction.
• Collaborate with data scientists and healthcare domain experts to curate and annotate datasets.
• Ensure high-performance deployment of NLP solutions on cloud platforms (AWS/Azure/GCP).
• Implement best practices in software development, MLOps, and CI/CD for NLP model deployment.
• Apply knowledge of medical terminologies and ontologies (UMLS, SNOMED, ICD-10).
Role: NLP Developer or Engineer
Location: Remote
Contract position.
Job Description:
• Develop and deploy NLP models to process unstructured medical documents and clinical text.
• Fine-tune and optimize transformer models (BERT, BioBERT, ClinicalBERT) for healthcare-specific applications.
• Build scalable and efficient NLP pipelines for document processing and information extraction.
• Collaborate with data scientists and healthcare domain experts to curate and annotate datasets.
• Ensure high-performance deployment of NLP solutions on cloud platforms (AWS/Azure/GCP).
• Implement best practices in software development, MLOps, and CI/CD for NLP model deployment.
• Apply knowledge of medical terminologies and ontologies (UMLS, SNOMED, ICD-10).
