Deep Learning Compiler Engineer
Quadric, Inc25 days ago
Remote, United States or Remote, CanadaSenior
Base Salary
$110k - $270k/yr
Responsibilities
- Drive the lowering and optimization of deep neural networks using Quadric technology.
- Develop mathematical and algorithmic optimizations for NP-hard problems.
- Collaborate with the software team on graph-based execution optimization for the Quadric architecture.
- Develop optimization passes for efficient lowering of deep learning and high-performance computing algorithms on the Quadric EPU.
- Build deep knowledge of the hardware platform and low-level software to improve application performance.
Requirements
- MS or PhD in Computer Science or a related field.
- At least eight years of industry experience.
- Strong background in numerical and/or algorithmic optimization.
- Ability to develop application-appropriate heuristics for NP-hard problems.
- Knowledge of classical and machine learning algorithms, including computer vision, DSP, and DNNs.
- Strong background in graphs and related algorithms.
- Preferred: proficiency in C++ 11 or later.
- Preferred: experience using or developing in TVM.
- Preferred: knowledge of compiler front-end and back-end techniques.
Benefits
- Remote work arrangement.
- Competitive base salary and meaningful equity eligibility.
- Medical, dental, and vision plan options starting on day one.
- 401(k) retirement plan.
- Flexible unlimited paid time off.
- Company-provided lunches and stocked kitchen when working in-office.
- Office location in downtown Burlingame within walking distance of Caltrain.
- Commuting support including monthly parking or Caltrain passes.
- Eligibility for a discretionary annual performance bonus as applicable to the role and level.
Tech Stack
Categories
About Quadric, Inc
Quadric licenses an AI processor architecture—the Chimera GPNPU—that runs neural-network inference and conventional C++ code on a single programmable core for edge devices. Its licensable IP targets automotive, industrial, robotics, and embedded systems, enabling customers to integrate a unified accelerator/processor into their SoCs. Founded in 2017 and headquartered in Burlingame, California, the privately held company was started by technologists from MIT and Carnegie Mellon.