Deep Learning Performance Architect

Responsibilities

• Benchmark and analyze performance of various machine learning/deep learning workloads across GPU- and NPU-based architectures
• Build and validate performance models, and deliver performance projections and insights for deep learning (LLM/GenAI) workloads on emerging architectures
• Identify architecture, software and system performance bottlenecks and propose actionable optimizations
• Explore and evaluate new software/hardware capabilities and translate them into measureable application gains
• Leverage AI agents to accelerate performance investigation and engineering workflows
• What we need to see:
• BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.,)
• 3+ years of working experience in relevant directions will be a plus
• Familiar with GPU or Accelerator-based deep learning platform and software stack
• A strong background in computer architecture
• Familiar with LLM or generative AI deep learning algorithms and kernel optimizations
• Experience in system architecture design and performance optimization
• Familiar with machine learning and deep learning frameworks
• Hands-on experience using AI agents to assist daily engineering work

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Company Intel

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