Senior Data Scientist - AI/ML/NLP
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist - AI/ML/NLP on a 6-month+ W2 contract, paying up to $65/hr. Remote U.S. candidates preferred. Requires 8–10+ years in AI/ML, experience building chatbots, strong Python skills, and cloud deployment expertise.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
520
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🗓️ - Date discovered
August 20, 2025
🕒 - Project duration
More than 6 months
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🏝️ - Location type
Remote
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📄 - Contract type
W2 Contractor
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🔒 - Security clearance
Unknown
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📍 - Location detailed
North Carolina, United States
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🧠 - Skills detailed
#SageMaker #API (Application Programming Interface) #Langchain #Deployment #ML (Machine Learning) #AI (Artificial Intelligence) #Python #Computer Science #Azure #AWS (Amazon Web Services) #NLP (Natural Language Processing) #Cloud #Data Science #Debugging #Hugging Face #"ETL (Extract #Transform #Load)" #AWS SageMaker #BERT #DevOps
Role description
Location: Remote (U.S.-based candidates; Raleigh/Durham location is a plus)
Contract Type: 6-month+ W2 Contract (potential to extend up to 18 months)
Pay Rate: up to $65/hr (W2)
Overview
We’re seeking a Senior Data Scientist to build a chatbot system from the ground up using cutting-edge large language models and Retrieval-Augmented Generation (RAG) techniques. This role is not about tweaking someone else’s model or managing post-deployment support. You’ll own architecture, modeling, training, evaluation, and deployment from day one.
This position is for hands-on builders who have stood up full-stack generative AI systems—not just contributed to them.
What You’ll Do
• Design and deploy chatbot capabilities end-to-end using LLMs and RAG architecture
• Architect multi-component workflows for semantic search, hallucination mitigation, and prompt engineering
• Train, fine-tune, and optimize LLMs (e.g., GPT-4, Claude, BERT, RoBERTa, T5) using modern frameworks
• Own code from prototype through production in monorepo environments with CI/CD pipelines
• Deploy and monitor solutions in AWS (preferred) or Azure
• Collaborate cross-functionally with engineers, product managers, and AI/ML teams
Must-Have Qualifications
• Built a production-grade chatbot or generative AI system from scratch
• 8–10+ years of experience in machine learning or AI, with deep NLP/LLM exposure
• 2+ years of applied experience with LLMs and RAG pipelines
• Strong hands-on skills in Python, API development, and debugging large-scale ML systems
• Proven experience with transformer-based architectures
• Familiarity with DevOps workflows and monorepo codebases
• Experience with cloud-based ML deployment, ideally in AWS (SageMaker, Bedrock)
Preferred
• Master’s or PhD in Computer Science, AI, Applied Math, or related field
• Experience with tools like LangChain, Hugging Face, Claude, LLaMA, or other foundation models
• Background in legal tech, healthcare, or domain-specific chatbot use cases
• Experience with multilingual LLMs or fine-tuning in niche domains
Location: Remote (U.S.-based candidates; Raleigh/Durham location is a plus)
Contract Type: 6-month+ W2 Contract (potential to extend up to 18 months)
Pay Rate: up to $65/hr (W2)
Overview
We’re seeking a Senior Data Scientist to build a chatbot system from the ground up using cutting-edge large language models and Retrieval-Augmented Generation (RAG) techniques. This role is not about tweaking someone else’s model or managing post-deployment support. You’ll own architecture, modeling, training, evaluation, and deployment from day one.
This position is for hands-on builders who have stood up full-stack generative AI systems—not just contributed to them.
What You’ll Do
• Design and deploy chatbot capabilities end-to-end using LLMs and RAG architecture
• Architect multi-component workflows for semantic search, hallucination mitigation, and prompt engineering
• Train, fine-tune, and optimize LLMs (e.g., GPT-4, Claude, BERT, RoBERTa, T5) using modern frameworks
• Own code from prototype through production in monorepo environments with CI/CD pipelines
• Deploy and monitor solutions in AWS (preferred) or Azure
• Collaborate cross-functionally with engineers, product managers, and AI/ML teams
Must-Have Qualifications
• Built a production-grade chatbot or generative AI system from scratch
• 8–10+ years of experience in machine learning or AI, with deep NLP/LLM exposure
• 2+ years of applied experience with LLMs and RAG pipelines
• Strong hands-on skills in Python, API development, and debugging large-scale ML systems
• Proven experience with transformer-based architectures
• Familiarity with DevOps workflows and monorepo codebases
• Experience with cloud-based ML deployment, ideally in AWS (SageMaker, Bedrock)
Preferred
• Master’s or PhD in Computer Science, AI, Applied Math, or related field
• Experience with tools like LangChain, Hugging Face, Claude, LLaMA, or other foundation models
• Background in legal tech, healthcare, or domain-specific chatbot use cases
• Experience with multilingual LLMs or fine-tuning in niche domains
