AI Hardware Intern — Hybrid, Next-Gen Inference Infra

Intel Corporation; Santa Clara (CA); Hybrid; USD 101,000 - 102,000; Part time

Benefits offered by this job

Stock bonuses

Health insurance

Retirement plan

Vacation

Job summary

Intel Corporation in Santa Clara, CA is seeking exceptional CS/EE/CE/AI/ML students for an AI Hardware Engineering internship focused on hardware/software co-design and AI inference infrastructure. You'll analyze model architectures, memory, and software stacks to optimize throughput, latency, power, and total cost of ownership.

The role is hands-on, research-driven, and collaborative within a highly technical team addressing AI hardware challenges; hybrid work model with internship

Qualifications

• Currently pursuing a PhD in Computer Science, Computer Engineering, Electrical Engineering, AI/ML, Systems Engineering, or related field.
• Strong foundation in computer architecture, OS, distributed systems, parallel computing, AI/ML systems.
• Experience with low-level languages like C/C++/CUDA or similar.

Responsibilities

• Conduct technical research on next-gen AI infrastructure (CPUs/GPUs/ASICs) and memory systems.
• Analyze GenAI workloads to understand hardware implications and performance bottlenecks.
• Develop technical models, simulations, or tools to evaluate hardware/software trade-offs.

Skills

CPU/GPU/AI accelerator

Hardware/Software co-design

Low-level programming

C/C++/CUDA

Profiling

Education

PhD student in Computer Science/Engineering/AI

Tools

Profiling tools

Job description

Intel Corporation in Santa Clara, CA is seeking exceptional CS/EE/CE/AI/ML students for an AI Hardware Engineering internship focused on hardware/software co-design and AI inference infrastructure. You'll analyze model architectures, memory, and software stacks to optimize throughput, latency, power, and total cost of ownership.

The role is hands-on, research-driven, and collaborative within a highly technical team addressing AI hardware challenges; hybrid work model with internship