AI/ML Architect contract C2C jobs at Woodland hills, CA

Job Title : AI/ML Architect

Location : Woodland hills ,CA (Onsite)

Duration : 12 Months

Senior AI/ML Architect with Hands on coding / development experience – GenAI & Cloud

Job Description :

Roles and Responsibilities:  

Architect and Design: Lead the design of scalable, secure, and high-performance AI/ML systems leveraging Agentic Layer A2A frameworks and MCP Protocols. 
Solution Engineering: Drive end-to-end solution development including vector embeddings, prompt engineering, and context engineering for enterprise-grade GenAI applications. 
Cloud Deployment: Architect and oversee deployment of AI/ML workloads on Azure Cloud, ensuring compliance, scalability, and cost optimization. 
Data Architecture: Design and optimize data pipelines and storage solutions using Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg. 
Application Development: Build and manage Azure Functions and Azure Container Apps for microservices-based AI solutions. 
Performance & Scalability: Define cloud-native architecture patterns, implement performance tuning, and ensure resilience across distributed systems. 
Domain Expertise: Apply deep knowledge of healthcare domain requirements, ensuring solutions meet regulatory standards (HIPAA, GDPR, etc.) and handle sensitive data securely. 
Technical Leadership: Mentor engineering teams, establish best practices, and conduct design/code reviews. 

Innovation & Research: Stay ahead of emerging GenAI, LLM/NLM trends, and integrate cutting-edge approaches into enterprise solutions. 
Evaluation Criteria (Critical Components)

1. Technical Depth

·         Ability to design and implement multi-agent AI systems.

·         Experience in LLM fine-tuning, embeddings, and context engineering.

·         Expertise in coding proficiency with production-grade systems in Python.

2. Architectural Vision

·         Ability to define enterprise-level AI/ML architecture aligned with cloud-native principles.

·         Experience in scalability, resilience, and performance optimization.

3. Cloud & Data Expertise

·         Hands-on deployment of AI workloads on Azure Cloud.

·         Strong knowledge of databases, search systems, and distributed storage.

4. Domain Knowledge

·         Familiarity with healthcare regulations and ability to design compliant solutions.

5. Leadership & Collaboration

·         Experience mentoring engineers, conducting reviews, and driving technical excellence.

·         Ability to collaborate with cross-functional teams including product, compliance, and operations.

6. Innovation & Research Orientation

·         Evidence of staying current with GenAI advancements and applying them to real-world problems.