Senior Generative AI Specialist/Data Scientist

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Generative AI Specialist/Data Scientist with 10+ years of experience in Generative AI and machine learning. It offers a long-term contract, remote work, and requires advanced Python skills, MLOps tools experience, and knowledge of ethical AI practices.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
August 9, 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
Redmond, WA
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Azure DevOps #Libraries #Transformers #Pandas #Compliance #NumPy #Databases #BERT #Python #Jira #Jupyter #Data Privacy #GDPR (General Data Protection Regulation) #DevOps #Visualization #Model Evaluation #Observability #AI (Artificial Intelligence) #GIT #Data Science #Programming #Docker #Matplotlib #Quality Assurance #BI (Business Intelligence) #Langchain #ML (Machine Learning) #Azure #Agile #Automated Testing #Hugging Face
Role description
Job Title: Senior Generative AI Specialist / Data Scientist Location: Remote Need 10yrs Experience Long Term About the Role We are looking for a highly experienced professional with 10+ years of hands-on experience in Generative AI (Gen AI), traditional machine learning, and quality assurance practices within data science. This role will be central to the development of state-of-the-art AI models that will directly influence core business and product strategies. Required Skills & Qualifications ·      Gen AI Expertise: Experience building, fine-tuning, and deploying Generative AI models (LLMs like GPT, BERT, T5, diffusion models, etc.). ·      Programming: Advanced Python skills with proficiency in libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Hugging Face Transformers, LangChain, etc. ·      Data Handling: Strong experience with large-scale data, ETL processes, and feature engineering. ·      MLOps Tools: Hands-on experience with Azure ML, VSCode, Jupyter Notebooks, Docker, and Git. ·      Model Evaluation: In-depth knowledge of evaluation metrics, bias detection, and responsible AI practices. ·      Visualization: Ability to create impactful visualizations using both traditional BI tools and code-based methods. ·      Soft Skills: Excellent analytical thinking, written and verbal communication, and a collaborative approach. Preferred Qualifications ·      Experience with LLM fine-tuning, embedding models, vector databases (e.g., FAISS, Pinecone), or Retrieval-Augmented Generation (RAG). ·      Familiarity with CI/CD pipelines for ML, model observability, and automated testing. ·      Understanding of data privacy, ethical AI, and compliance frameworks (e.g., GDPR, HIPAA, etc.). ·      Experience working in Agile teams and using project tracking tools like Jira, Confluence, or Azure DevOps.