Q

Quadric

GPNPU hardware and software for ML

Forward Deployed Engineer

AI Application EngineeringUpdated on Nov 9
Full-timeBurlingame, CA, USA

About the Job

Requirements

  • Strong C++ and Python skills, including experience writing performance-critical code for a constrained target such as a DSP, NPU, GPU, or embedded SoC.
  • Systems-level performance intuition, including memory bandwidth, data movement, and cycle-level reasoning, with the ability to interpret profiling results.
  • Ability to solve problems independently using a methodical and empirical approach.
  • Ability to work in ambiguity without an established playbook.

Responsibilities

  • Convert 2–3 active customer evaluations into committed design wins by getting customer workloads running at target latency and accuracy on Chimera.
  • Port customer workloads onto Chimera by architecting and adapting them, profiling performance, and writing custom kernels when required.
  • Work on-site and remotely with customer engineering teams to debug failures, meet benchmark targets, and guide model-architecture tradeoffs.
  • Drive customer evaluations end-to-end, from the first technical conversation through design win.
  • Codify lessons into reusable assets, including SDK skills, porting playbooks, and agentic content, to make subsequent engagements faster.
  • Build applications and benchmark collateral to support future customer engagements.
  • Partner with engineering and product teams to relay customer learnings and shape the roadmap.
  • Contribute skills and playbooks to Quadric's agentic FDE toolset.

Desired Qualifications

  • Prior experience or a title in field applications engineering, sales engineering, or forward deployed engineering, or startup experience as the de facto owner of an end-to-end implementation.
  • Familiarity with agentic development tools such as Claude Code and MCP, or strong enthusiasm to adopt them.
  • Background at NPU/edge-AI IP and silicon companies.
  • Background at inference-focused startups in field/customer engineering or kernel teams.
  • Forward deployed engineering experience; candidates with embedded or machine-learning systems backgrounds are also considered.
  • Experience at technical trading arms optimizing kernels or hardware for speed.
  • Big-firm consulting background, provided the candidate personally performed hands-on technical work rather than managing it.

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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