Q

Quadric

GPNPU hardware and software for ML

Deep Learning Compiler Intern

Systems Software EngineeringConfirmed live in the last 24 hours
InternshipBurlingame, CA, USA$50 - $57 /hr

About the Job

Requirements

  • Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or a related field.
  • Demonstrate strong proficiency in Python and C++.
  • Have a foundational understanding of compiler concepts, including intermediate representations, dataflow analysis, and transformation passes.
  • Be comfortable reading and reasoning about large, unfamiliar codebases.
  • Demonstrate problem-solving and debugging capability, and communicate technical information clearly.

Responsibilities

  • Help build and extend compiler passes that lower neural network intermediate representations to code targeting the General Purpose Neural Processing Unit.
  • Diagnose compilation issues by tracing problems from generated C++ back through the pipeline, and use intermediate-representation dumps and static analyses to investigate compilation failures and performance regressions.
  • Work alongside senior engineers to improve compiler decisions to reduce data movement and increase core utilization.
  • Partner with the kernel, hardware, and data science teams to align compiler features with model requirements and hardware constraints.
  • Contribute to test infrastructure, debugging utilities, and developer ergonomics across the CGC pipeline and runtime.

Desired Qualifications

  • Have coursework or project experience with compilers, program analysis, or domain-specific languages.
  • Have exposure to machine learning compiler frameworks such as TVM, MLIR, XLA, Glow, or IREE.
  • Be familiar with neural network quantization, fixed-point arithmetic, or numerical analysis.
  • Have experience with hardware-aware code generation for accelerators such as GPUs, DSPs, or NPUs.
  • Have some exposure to assembly or low-level code generation.
  • Have previous internship experience in compilers, machine learning systems, or performance engineering.

About the Company

Quadric

GPNPU hardware and software for ML

Quadric.io provides an integrated hardware-software platform for ML on System-on-Chips, centered on its Chimera General-Purpose Neural Processing Unit (GPNPU). Developers write ML code in C, which is compiled by the Chimera LLVM C Compiler, simulated with the Chimera Instruction Set Simulator (ISS), and deployed via a Software Development Kit (SDK) that supports design, profiling, and execution on Chimera. The solution is a single, end-to-end pipeline that eliminates the need to partition code across DSPs/GPUs and CPUs, offering tightly integrated hardware and software tools that can run a wide range of C-based neural-network operations. Quadric.io aims to simplify and accelerate the design of ML-enabled SoCs for semiconductor developers and manufacturers, enabling faster time-to-market and better ML performance through its cohesive hardware-software stack.

Company size
51-200
Company stage
Series C
Total funding
$94.3M
Headquarters
Burlingame, CA
Founded
2017

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