# Deep Learning Compiler Engineer (New Grad)

**Company:** [Quadric](https://hotfix.jobs/companies/quadric)
**Location:** Burlingame, CA
**Role:** ML Engineering
**Salary:** $120k – $160k/yr
**Experience:** 0+ years
**Skills:** Python, C++, Onnx, Relay Ir, Tvm, Mlir, Xla, Glow, Iree, Intermediate Representations, Dataflow Analysis, Ir Transformations, Neural Network Quantization, Fixed-Point Arithmetic
**Posted:** 2026-05-06

> Develops and optimizes deep learning compiler passes for Quadric's GPNPU, lowering ONNX models through Relay IR to efficient C++ code. Requires new grad-level proficiency in Python, C++, and compiler concepts like IR transformations and debugging.

## Job Description

## Responsibilities
- Own compiler passes.
- Design and implement IR transformations that lower neural network IR to GPNPU-targeted code.
- Take pieces of the pipeline as yours and maintain them.
- Debug end-to-end. Diagnose compilation issues by tracing problems from generated C++ back through the pipeline.
- Use IR dumps, static analyses, and the ISS to root-cause compilation failures and performance regressions.
- Improve compiler decisions. Work with senior engineers to reduce data movement, improve core utilization, and tighten the gap between what the hardware can do and what we currently emit.
- Collaborate across teams. Partner with the kernel, hardware, and data science teams to align compiler features with real model requirements and hardware constraints.
- Strengthen the toolchain. Contribute to test infrastructure, debugging utilities, and developer ergonomics across the CGC pipeline and runtime.

## Requirements
### Must-Haves
- Bachelor's, Master's, or PhD in Computer Science, Electrical Engineering, or a related field, completed within the past year (or completing within the next six months).
- Strong proficiency in **Python** and **C++**.
- Solid grasp of compiler concepts: intermediate representations, dataflow analysis, transformation passes, and lowering.
- Comfort reading and reasoning about large, unfamiliar codebases.
- Strong debugging and problem-solving skills, with the ability to communicate findings clearly in writing and review.

### Nice-to-Haves
- Coursework, research, or significant project experience in compilers, program analysis, or domain-specific languages.
- Hands-on exposure to ML compiler frameworks such as **TVM**, **MLIR**, **XLA**, **Glow**, or **IREE** — bonus if you have written a non-trivial pass.
- Familiarity with neural network quantization, fixed-point arithmetic, or numerical analysis for ML.
- Experience with hardware-aware code generation for accelerators (**GPU**, **DSP**, **NPU**).
- Some exposure to assembly, instruction scheduling, or low-level code generation.
- Prior internship experience in compilers, ML systems, or performance engineering.
- Published research or open-source contributions in compilers or ML systems.

## Compensation
- Base salary range: **$120,000 - $160,000**.
- Equity and discretionary annual performance bonus.
- Medical, dental, and vision plan options starting on day one.
- 401(k) retirement plan.
- Flexible paid time off (unlimited, non-accrual).

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