Rivago Infotech Inc
AI/ML Architect
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an AI/ML Architect on a contract basis for 40 hours per week, offering $80.00 - $85.00 per hour. Requires expertise in healthcare data systems, transformer-based models, MLOps, and compliance with HIPAA. On-site location.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
680
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🗓️ - Date
December 5, 2025
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Tarrytown, NY 10591
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🧠 - Skills detailed
#Data Science #FHIR (Fast Healthcare Interoperability Resources) #Scala #FastAPI #Kubernetes #Generative Models #GDPR (General Data Protection Regulation) #PyTorch #Cloud #Azure #Microservices #Hugging Face #AWS (Amazon Web Services) #Langchain #Deep Learning #Deployment #Databases #Python #TensorFlow #MLflow #AI (Artificial Intelligence) #Leadership #"ETL (Extract #Transform #Load)" #GCP (Google Cloud Platform) #Compliance #ML (Machine Learning)
Role description
We are seeking a visionary and hands-on Machine Learning & Generative AI Architect to lead the design, development, and deployment of cutting-edge AI/ML and GenAI solutions in the healthcare and biotech domain. The ideal candidate will have deep expertise in transformer-based architecture, generative models (LLMs, GANs, Diffusion Models), and MLOps, with a strong understanding of regulatory compliance (e.g., HIPAA) and healthcare data systems.
Key Responsibilities:
Generative AI & LLMs
Architect and implement transformer-based generative models tailored for biomedical data, optimizing training pipelines for domain-specific nuances.
Compare and evaluate generative models (GANs, VAEs, Diffusion Models) for synthetic medical image generation, selecting the most suitable based on use case.
Design scalable GenAI systems for generating synthetic patient records with built-in HIPAA compliance and data anonymization.
Fine-tune pre-trained LLMs for domain-specific applications such as drug discovery, clinical trial summarization, and medical literature analysis.
Develop strategies to mitigate hallucinations in LLMs, especially for clinical decision support systems.
System Architecture & Integration
Design GenAI-powered platforms that integrate seamlessly with existing EHR systems, supporting real-time inference and secure data exchange.
Define and implement APIs for GenAI services optimized for multi-cloud and hybrid environments, ensuring scalability and interoperability.
Ensure robust model versioning, traceability, and reproducibility in compliance with regulatory standards.
MLOps & Deployment
Lead the development of CI/CD pipelines and MLOps workflows for model training, evaluation, and deployment.
Collaborate with data scientists and engineers to optimize model performance using TensorFlow, PyTorch, and Hugging Face.
Manage cloud-native microservices using Python, FastAPI, and container orchestration tools (e.g., Kubernetes).
Required Skills & Qualifications:
Strong foundation in AI/ML, deep learning, and GenAI architectures.
Hands-on experience with LLMs, RAG systems, LangChain, LangGraph, and vector databases.
Proficiency in Python, FastAPI, and cloud platforms (AWS, Azure, GCP).
Experience with MLOps tools and practices (MLflow, Kubeflow, CI/CD).
Deep understanding of healthcare data standards (FHIR, HL7) and compliance frameworks (HIPAA, GDPR).
Excellent communication and leadership skills.
Job Type: Contract
Pay: $80.00 - $85.00 per hour
Expected hours: 40 per week
Work Location: In person
We are seeking a visionary and hands-on Machine Learning & Generative AI Architect to lead the design, development, and deployment of cutting-edge AI/ML and GenAI solutions in the healthcare and biotech domain. The ideal candidate will have deep expertise in transformer-based architecture, generative models (LLMs, GANs, Diffusion Models), and MLOps, with a strong understanding of regulatory compliance (e.g., HIPAA) and healthcare data systems.
Key Responsibilities:
Generative AI & LLMs
Architect and implement transformer-based generative models tailored for biomedical data, optimizing training pipelines for domain-specific nuances.
Compare and evaluate generative models (GANs, VAEs, Diffusion Models) for synthetic medical image generation, selecting the most suitable based on use case.
Design scalable GenAI systems for generating synthetic patient records with built-in HIPAA compliance and data anonymization.
Fine-tune pre-trained LLMs for domain-specific applications such as drug discovery, clinical trial summarization, and medical literature analysis.
Develop strategies to mitigate hallucinations in LLMs, especially for clinical decision support systems.
System Architecture & Integration
Design GenAI-powered platforms that integrate seamlessly with existing EHR systems, supporting real-time inference and secure data exchange.
Define and implement APIs for GenAI services optimized for multi-cloud and hybrid environments, ensuring scalability and interoperability.
Ensure robust model versioning, traceability, and reproducibility in compliance with regulatory standards.
MLOps & Deployment
Lead the development of CI/CD pipelines and MLOps workflows for model training, evaluation, and deployment.
Collaborate with data scientists and engineers to optimize model performance using TensorFlow, PyTorch, and Hugging Face.
Manage cloud-native microservices using Python, FastAPI, and container orchestration tools (e.g., Kubernetes).
Required Skills & Qualifications:
Strong foundation in AI/ML, deep learning, and GenAI architectures.
Hands-on experience with LLMs, RAG systems, LangChain, LangGraph, and vector databases.
Proficiency in Python, FastAPI, and cloud platforms (AWS, Azure, GCP).
Experience with MLOps tools and practices (MLflow, Kubeflow, CI/CD).
Deep understanding of healthcare data standards (FHIR, HL7) and compliance frameworks (HIPAA, GDPR).
Excellent communication and leadership skills.
Job Type: Contract
Pay: $80.00 - $85.00 per hour
Expected hours: 40 per week
Work Location: In person
