AI/ML Solutions Architect

Requirements

• Solution Design: Ability to architect end-to-end ML systems for diverse business problems
• ML Lifecycle: Deep understanding of the full ML lifecycle from data to deployment
• System Design: Experience designing scalable, production-grade ML architectures
• Trade-off Analysis: Ability to evaluate technical approaches (cost, performance, complexity)
• Feasibility Assessment: Quickly assess if ML is an appropriate solution for a problem

Additional Information

As an ML Solutions Architect, you'll be the technical bridge between clients and delivery teams. You'll lead pre-sales technical discussions, design ML architectures that solve business problems, and ensure solutions are feasible, scalable, and aligned with client needs. This is a highly client-facing role requiring both deep technical expertise and strong communication skills.

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Company Intel

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