- Company Name
- Arkhya Tech. Inc.
- Job Title
- AI/ML Architect
- Job Description
-
Job Title: AI/ML Architect
Role Summary: Design, build, and maintain generative AI solutions for biomedical data, ensuring compliance, scalability, and seamless integration with healthcare systems.
Expactations: Lead AI/ML strategy and model lifecycle from research to production; develop domain‑specific transformer and generative models; enforce regulatory compliance; collaborate with cross‑functional teams; mentor and drive continuous improvement in AI/ML processes.
Key Responsibilities
- Architect transformer‑based generative models for biomedical data, optimizing pipelines for domain nuances.
- Evaluate GANs, VAEs, and diffusion models for synthetic medical image generation; select appropriate models per use case.
- Design HIPAA‑compliant GenAI systems for synthetic patient records with automated anonymization.
- Fine‑tune pre‑trained LLMs for drug discovery, clinical trial summarization, and literature analysis.
- Implement strategies to mitigate hallucinations in LLMs for clinical decision support.
- Build GenAI platforms that integrate with EHR systems, enabling real‑time inference and secure data exchange.
- Define and implement multi‑cloud APIs for GenAI services, ensuring scalability and interoperability.
- Maintain robust model versioning, traceability, and reproducibility in line with regulatory standards.
- Lead CI/CD and MLOps pipelines for model training, evaluation, and deployment.
- Collaborate with data scientists and engineers to optimize performance using TensorFlow, PyTorch, and Hugging Face.
- Manage cloud‑native microservices with Python, FastAPI, Docker, and Kubernetes.
- Document architecture, governance, and compliance artifacts.
Required Skills
- Python, FastAPI, TensorFlow, PyTorch, Hugging Face.
- Deep knowledge of LLMs, RAG, LangChain, LangGraph, and vector databases.
- MLOps tools: MLflow, Kubeflow, CI/CD, Docker, Kubernetes.
- Cloud platforms: AWS, Azure, GCP.
- Healthcare data standards: FHIR, HL7; regulatory frameworks: HIPAA, GDPR.
- Strong analytical, problem‑solving, leadership, and communication skills.
- Experience mentoring or leading cross‑functional AI/ML teams.
Required Education & Certifications
- Bachelor’s or Master’s in Computer Science, Electrical Engineering, Data Science, or related field (advanced degree preferred).
- Relevant certifications: AWS Certified Machine Learning – Specialty, Azure AI Engineer Associate, GCP Professional Machine Learning Engineer, or MLOps certification.