Quadric Forward Deployed Engineer owns the technical path from customer evaluation to silicon design for the Quadric Chimera GPNPU. Works across the stack including quantization, custom kernels, and compiler tooling.
Responsibilities
You'll own the technical path from customer evaluation to silicon design and win on a genuinely novel architecture, the Quadric Chimera GPNPU, which runs everything from CNNs to LLMs to arbitrary C++ on one core, with no fallback processor. Unlike a FAANG solutions role, you'll work the entire stack: quantization, custom kernels, and compiler and your fingerprints will be on chips that ship in cars, cameras, and network appliances.
At a Series C company, every design win has outsized impact. Our FDEs also build with frontier agentic tooling (Claude Code–based agentic workflows) — you won't just be supporting the product, you'll be inventing how edge-AI field engineering is done.
Own the Technical Path to Design Win
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 — architect, adapt, profile, and write custom kernels when required.
Embed with Customer Engineering Teams
Work on-site and remotely with customer engineering teams: debug failures, hit benchmark targets, and guide model-architecture tradeoffs.
Drive evaluations forward end-to-end, from first technical conversation through design win.
Build the Agentic FDE Toolkit
Codify what you learn into reusable assets — SDK skills, porting playbooks, and agentic content — so each subsequent engagement moves faster than the last.
Build applications and benchmark collateral that support future customer engagements.
Close the Loop Internally
Qualification
Strong C++ and PythonPrior FAEBig-firm consulting background
Required
Strong C++ and Python; has written performance-critical code for a constrained target (DSP, NPU, GPU, or embedded SoC).
Systems-level performance intuition — memory bandwidth, data movement, cycle-level reasoning — and can read a profile and know where the time went.
High agency and independent problem-solving; methodical and empirical rather than theoretical.
Comfortable operating without a playbook and in ambiguity — this role is still being defined.
Preferred
Prior FAE, Sales Engineering, or FDE title — or startup experience as the de facto owner of an end-to-end implementation.
Familiarity with agentic dev tooling (Claude Code, MCP) — or strong enthusiasm to adopt it.
Background at NPU/edge-AI IP and silicon companies
Background at inference-focused startups in field/customer engineering or kernel teams.
FDE experience — candidates with embedded or ML-systems backgrounds.
Experience at technical trading arms optimizing kernels or hardware for speed
Big-firm consulting background, provided the candidate personally did the hands-on technical work rather than managing it.
