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Hire AI Chip Architects
Hire Pre-Vetted AI Chip Architecture Engineers
Hire AI-verified AI chip architects and NPU designers. Tensor cores, HBM integration, systolic arrays. First shortlist in 72 hours.
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$160–280/hr
First shortlist in <72 hours
Zero engineer commission
Why AI Chip Architecture Hiring Is Broken
AI chip architects design the specialized hardware accelerators driving the AI revolution: neural processing units, tensor cores, systolic arrays, and the memory hierarchies that feed them. This is the fastest-growing specialization in semiconductor design.
AI chip architecture requires a unique blend of machine learning understanding and hardware design expertise. Engineers must optimize for inference latency, training throughput, power efficiency, and memory bandwidth simultaneously. ShawSilicon verifies this rare combination of skills.
Key Skills & Tools
Core Skills
NPU/TPU ArchitectureTensor Core DesignSystolic ArraysHBM/HBM2E IntegrationDataflow OptimizationQuantization-Aware DesignOn-Chip InterconnectsDMA Engines
EDA Tools & Platforms
SystemCTLMGem5NVDLATensorRTCustom RTL frameworks
Roles We Fill
- AI Chip Architect
- NPU Design Engineer
- ML Hardware Engineer
- AI Accelerator RTL Designer
- DNN Hardware Optimization Engineer
How ShawSilicon Works
Step 1: Post your AI Chip Architecture role with required skills, rate range, and timeline.
Step 2: We match you with pre-vetted engineers who have passed our AI Technical Interview in AI Chip Architecture. You see verified scores, not just resumes.
Step 3: Interview your shortlist and start the engagement. Average time from posting to first shortlist: under 72 hours.
Frequently Asked Questions
What AI chip skills does ShawSilicon test?
Our AI interview covers accelerator architecture concepts, dataflow optimization, memory hierarchy design for ML workloads, quantization-aware hardware, and the trade-offs between different compute array topologies (systolic, CGRA, dataflow).
Do your engineers have experience with specific AI accelerator platforms?
Yes. Our engineers have worked on custom NPUs, NVDLA-based designs, Google TPU-style architectures, and FPGA-based AI accelerators. Many have experience with both training and inference hardware.
Why are AI chip architects the most expensive specialization?
AI chip architecture sits at the intersection of two high-demand fields: semiconductor design and machine learning. Engineers with real tape-out experience on AI accelerators are extremely rare, commanding $160–280/hr.
Can I hire AI chip architects for FPGA-based accelerators?
Yes. Many AI chip architects on ShawSilicon have experience implementing neural network accelerators on FPGAs using HLS, custom RTL, or hybrid approaches.
What memory technologies do your AI chip engineers work with?
Our engineers have experience with HBM, HBM2E, LPDDR5, GDDR6, and on-chip SRAM hierarchies. Memory bandwidth optimization is a core competency for AI chip design.
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