Role: AI/ML Architect
Location: Tarrytown NY 10591
Role Overview:
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.
Role: AI/ML Architect Location: Tarrytown NY 10591 Role Overview: 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 w...
Role: AI/ML Architect
Location: Tarrytown NY 10591
Role Overview:
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.
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