We are looking for Senior AI/ML Engineer – GenAI & Cloud Solutions in Woodland hills, CA - Onsite

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Aswin

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Jul 1, 2026, 11:11:42 AM (2 days ago) Jul 1
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We are looking for Senior AI/ML Engineer – GenAI & Cloud Solutions in Woodland hills, CA - Onsite

 

Duration: Long term contract

 

Key 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.

 

Required Skills & Expertise:

 

                       Agentic Layer & Protocols: Hands-on expertise with Agentic Layer A2A frameworks and MCP Protocol for multi-agent orchestration.

                       AI/ML Engineering: Strong background in vector embeddings, prompt engineering, context engineering, and fine-tuning LLMs.

                       GenAI & LLM Concepts: Deep understanding of Generative AI, Natural Language Models (NLM), and Large Language Models (LLM).

                       Programming: Advanced proficiency in Python; exposure to Java/Go is a plus.

                       Cloud Proficiency: Strong experience with Azure Cloud services, including deployment, monitoring, and scaling.

                       Databases: Expertise in Azure AI Search, Redis, Cosmos DB; familiarity with Blob Storage and Iceberg is advantageous.

                       Cloud-Native Architecture: Solid grasp of microservices, containerization, serverless computing, scalability, and performance optimization.

                       Healthcare Domain: Experience working with regulated data environments and compliance frameworks.

 

Evaluation Criteria (Critical Components)

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.

 

Architectural Vision

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

•              Experience in scalability, resilience, and performance optimization.

 

Cloud & Data Expertise

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

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

 

Domain Knowledge

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

 

Leadership & Collaboration

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

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

 

Innovation & Research Orientation

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

 

Preferred Qualifications:

•              Bachelors or master’s in computer science, AI/ML, or related field.

•              Certifications in Azure Solutions Architect or AI Engineering.

•              Publications, patents, or contributions to open-source AI/ML projects.

Aswin

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Jul 1, 2026, 1:31:59 PM (2 days ago) Jul 1
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