Analyze and optimize code execution on Quadric's innovative neural processing unit architecture, bridging software and hardware for peak performance.
Quadric has created an innovative general purpose neural processing unit (GPNPU) architecture. Quadric's co-optimized software and hardware is targeted to run neural network (NN) inference workloads in a wide variety of edge and endpoint devices, ranging from battery operated smart-sensor systems to high-performance automotive or autonomous vehicle systems. Unlike other NPUs or neural network accelerators in the industry today that can only accelerate a portion of a machine learning graph, the Quadric GPNPU executes both NN graph code and conventional C++ DSP and control code.
As a Senior Performance Architect, you will be the critical link between software and hardware, responsible for understanding how code executes on Quadric's architecture and identifying opportunities for optimization. You will analyze workloads from high-level C++ and Python down through generated assembly to pinpoint performance bottlenecks. This is a hands-on role: beyond analysis, you will prototype solutions yourself - whether that means writing optimized code, modifying compiler passes, or building proof-of-concept implementations to validate proposed fixes before handing off to the appropriate team for productization.
This role requires regular work from the Quadric office in Burlingame, CA, a minimum of 2–3 days per week, with some weeks requiring more days onsite based on business needs. Candidates must be able to commute to the office.
Requirements
Benefits
Free Meals & Snacks
When working in-office, enjoy company-provided lunches and a stocked kitchen
Health Insurance
Medical, dental, and vision coverage starting on day one
Commuting support
Support for commuting, including monthly parking or Caltrain passes
Paid Time Off
Flexible paid time off (unlimited, non-accrual) to support work-life balance
Quadric builds a groundbreaking general purpose neural processing unit (GPNPU) architecture that enhances the performance of neural network inference on edge devices. Our technology caters to developers and businesses looking to leverage AI in real-time applications, distinguishing itself by combining supercomputing capabilities with the immediacy required by the edge.
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