Edge AI Kernel Engineer - Real-Time Inference

Quadric; Burlingame (CA); Hybrid; CAD 155,000 - 382,000; Full time

Benefits offered by this job

Competitive salary

Meaningful equity

Medical/Dental/Vision

401(k)

Unlimited PTO

Job summary

Quadric is seeking an AI Kernel Engineer to enable a broad set of AI kernels and operators on our GPNPU platform. You will optimize kernel performance, profile workloads, and debug complex code paths across CUDA, DSP, NEON and Triton-lang, while collaborating with teams to advance the inference stack.

Ideal candidates have 5+ years in AI kernel development, strong C/C++ and Python skills, and a proven track record of optimizing high-performance kernels for edge devices.

Qualifications

• Bachelor's or Master's in CS and/or Electrical Engineering.
• 5+ years experience in AI kernel development and optimization.
• Experience with model/kernel inference profiling.
• Experience with CUDA, DSP, NEON, or Triton-lang.
• Proficiency in C/C++ and Python; assembly language a plus.
• Strong problem solving, debugging, and communication.

Responsibilities

• Develop AI/LLM kernels/operators on Quadric platform for efficient inference.
• Optimize the kernel performance for different hardware configurations and workloads.
• Profile and analyze kernel performance in terms of compute, data and parallelism; identify micro-architecture and software bottlenecks and provide optimization solutions.
• Optimize kernel C/C++ codes, maximize hardware utilization.
• Collaborate across related areas of the AI inference stack to support team and business priorities.
• Make improvement to Quadric toolchain, compiler and runtime.
• Provide technical support and documents to customers and developer community

Skills

AI kernel dev

C/C++

Python

Profiling

Problem solving

Communication

Education

CS or EE degree

Job description

Quadric is seeking an AI Kernel Engineer to enable a broad set of AI kernels and operators on our GPNPU platform. You will optimize kernel performance, profile workloads, and debug complex code paths across CUDA, DSP, NEON and Triton-lang, while collaborating with teams to advance the inference stack.

Ideal candidates have 5+ years in AI kernel development, strong C/C++ and Python skills, and a proven track record of optimizing high-performance kernels for edge devices.