Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Senior, niche role but metro location and broad skill list attract moderate competition.
Highly technical ML/LLM architecture skills transfer across industries, though healthcare domain experience is beneficial.
Explicit 15+ years requirement plus specific ML/LLM, MLOps, and cloud stack mandates make filters high.
Own design and implementation of microservice architecture and API management for AI solution deployment.
Develop scalable AI pipelines including predictive modeling, LLM architectures, and MLOps practices with cloud and container orchestration.
Collaborate with cross-functional teams to integrate AI/ML models, conduct A/B testing, and optimize large-scale AI/ML infrastructure and deployment.
Minimum 15+ years experience in Data Science and GenAI end-to-end architecture solution design.
Bachelor’s degree in any Engineering discipline; Masters or PhD in data science or computer science is nice to have.
Technical skills required: Python, microservices, LLM frameworks, MLOps tools, Kubernetes, Terraform/CloudFormation, CI/CD pipelines, cloud platforms (AWS/GCP/Azure).
Experience with scalable architectures meeting 99.99% availability, NFRs (disaster recovery, RTO, RPO), and advanced LLM deployment techniques.
Senior architect-level professional with deep expertise in AI/ML system design, large language models, and microservices-based cloud architectures.
Experienced in handling complex, enterprise-grade AI/ML infrastructure with strong capabilities in MLOps, container orchestration, and performance optimization.
Proven ability to bridge domain knowledge with AI engineering to create innovative healthcare AI solutions and handle strategic design decisions while collaborating cross-functionally.