NLP Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an NLP Engineer with a contract length of "X months" and a pay rate of "$X/hour". Requires strong experience in NLP, Regular Expressions, and knowledge of medical terminologies. Must develop and deploy healthcare-specific NLP models on cloud platforms.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
September 17, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Unknown
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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
#GCP (Google Cloud Platform) #Azure #Regular Expressions #Datasets #ML (Machine Learning) #BERT #Model Deployment #Cloud #Scala #Deployment #"ETL (Extract #Transform #Load)" #Data Science #AWS (Amazon Web Services) #NLP (Natural Language Processing)
Role description
Note: Candidate must have experience with Regular Expressions (Regex). Looking for someone with a strong data-focused background, not primarily involved in LLMs or Machine Learning.
Strong Exp in NLP
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).
Note: Candidate must have experience with Regular Expressions (Regex). Looking for someone with a strong data-focused background, not primarily involved in LLMs or Machine Learning.
Strong Exp in NLP
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).
