Healthcare AI Engineer – LLM & Machine Learning

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Healthcare AI Engineer focusing on ML and LLMs, with a contract length of "unknown". Pay rate is $65-$75/hr. Remote work requires recent healthcare experience and proficiency in ML frameworks, LLMs, and HIPAA compliance.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
600
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🗓️ - Date discovered
August 30, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
Remote
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📄 - Contract type
1099 Contractor
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🔒 - Security clearance
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Python #Data Privacy #Azure #Data Science #Model Deployment #Cloud #NLP (Natural Language Processing) #Hugging Face #Libraries #TensorFlow #AWS (Amazon Web Services) #Deployment #PyTorch #FHIR (Fast Healthcare Interoperability Resources) #Security #MLflow #Data Engineering #Code Reviews #GCP (Google Cloud Platform) #ML (Machine Learning) #AI (Artificial Intelligence) #Compliance
Role description
Job Role: AI/ML Engineer (Healthcare) Location: Remote Pay Rate: $65-$75/hr. on C2C/1099 Need someone with healthcare background Recent 5 years in healthcare domain NOTE: This is the same position that was posted 2–3 months ago. At that time, one candidate was placed, but as the team continues to evolve, we are looking to add one more candidate with a stronger focus on ML. Job Description: We are seeking a highly skilled AI Engineer with expertise in Machine Learning (ML) modeling and Large Language Models (LLMs) to join a cutting-edge healthcare project. The ideal candidate will have experience tuning and integrating open-source LLMs and supplementing them with custom ML models when necessary. You will work closely with data scientists, software engineers, and healthcare stakeholders to build intelligent, compliant solutions using sensitive patient data. Key Responsibilities: • Utilize and fine-tune open-source LLMs (OpenAI, Hugging Face models) for healthcare-specific use cases. • Identify scenarios where traditional ML models are required to enhance or complement LLM functionality. • Develop, test, and maintain ML models tailored to patient-centric solutions. • Ensure all AI models and data handling practices are HIPAA-compliant. • Collaborate with cross-functional teams including product managers, data engineers, and security analysts. • Optimize model performance for production environments. • Participate in code reviews and contribute to continuous model and pipeline improvement. Required Qualifications: • Strong hands-on experience with Machine Learning frameworks (TensorFlow, PyTorch, Scikit-learn). • Proficiency in working with open-source LLMs and experience in prompt engineering, fine-tuning, or customizing pre-trained models. • Solid understanding of ML lifecycle, from data preprocessing to model deployment. • Familiarity with healthcare data formats (HL7, FHIR) and HIPAA compliance requirements. • Experience working with cloud platforms (AWS, Azure, or GCP) for deploying ML/LLM solutions. • Proficient in Python and relevant ML/AI libraries. • Ability to work independently in a remote, collaborative environment. Preferred Qualifications: • Previous experience in the healthcare domain. • Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow). • Experience with data privacy and security in AI applications. • Exposure to medical NLP use cases is a plus.