Frontend Compiler Engineer II

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Hiring Remotely in Tokyo
Remote
Internship
Artificial Intelligence • Software
The Role

Frontend Compiler Engineer II (mid-career)
Introduction

Edgecortix Inc. is seeking strong software engineers to work as part of our deep-learning compiler team. If you have a strong desire to build next-generation AI chips and systems, join us, and let's reshape the future of AI at the edge.

About Edgecortix

At Edgecortix we are a deep-tech startup revolutionizing edge computing with artificial intelligence and novel high-efficiency silicon-on-chip design. Originating from multiple years of research, our unique AI hardware & software co-exploration engine and Dynamic Neural Accelerator ™ AI processor IP are geared towards positively disrupting the rapidly growing artificial intelligence edge hardware space and bringing the power of AI and machine learning to all kinds of devices.

The Team

As a team, we are working to define and solve the hardest problems in AI including computer vision, speech, and natural language, geared towards real-time capabilities on small to medium-form factor devices. We originated out of multiple years of research, as such at our core we value learning, intellectual curiosity, and self-starters. We have the ambitious goal of enabling cloud-level performance with significantly better energy efficiency for AI inference at the edge.

Your Role and Responsibilities

In this role, working closely with our hardware and ML engineers, you will extend our compiler and software toolchain for deploying machine learning models with high performance and flexibility on our proprietary AI hardware accelerator.

Minimum Qualifications

  • Bachelor's in Computer Engineering, Computer Science and/or Electrical Engineering.
  • 5+ years of Software Engineering experience.
  • 3+ years experience in writing production-quality C++.
  • 2+ years experience developing Python, including pip packaging and C++ bindings.
  • 2+ years of experience on ML graph optimization passes
  • 1+ years experience using the MLIR/LLVM framework.
  • Experience with code management using Git and familiarity with GitHub/GitLab PR flow.
  • Exposure to CI/CD tools such as Jenkins.
  • Knowledge of ML quantization techniques and mixed precision inference.
  • Strong debugging and analysis skills, for root causing complex issues.

Preferred Qualifications

  • Knowledge of neural networks, with hands-on experience using ML frameworks such as TensorFlow/PyTorch/ONNX.
  • Knowledge of Convolutional Neural Networks (CNNs), RNN/LSTMs or Transformers (LLMs) and familiarity with multi-modal ML models.
  • Experience developing embedded software, preferably for ASIC or on-device ML.
  • Experience with low level machine specific code generation (e.g. x86, RISC-V or similar)
  • Familiarity with code generation for microcode generation (e.g. video codec firmware, CPU microcode etc)
  • Experience with vectorization and parallel programming models such as OpenMP or CUDA/OpenCL.
  • Previous experience working in an Agile environment, and collaborating with multidisciplinary teams across different time zones.
  • Experience with writing performance or functional simulators, and interpreters

What’s in it for you?

Make a difference: you will have the opportunity to join a well-funded fabless AI semiconductor startup that is disrupting the AI software and hardware co-design space. Be an integral part of its growth and momentum.

Benefits and Perks

  • Highly competitive salary and stock options
  • Flex work time and ability to work fully remotely from anywhere
  • Support for obtaining visa and relocation support (in case of Japan)
The Company
HQ: San Francisco, California
38 Employees
On-site Workplace
Year Founded: 2019

What We Do

EdgeCortix is an Edge Artificial Intelligence (AI) Platform company, pioneering the future of the connected intelligent edge. It was founded in 2019 with the radical idea of taking a software first approach, while designing an artificial intelligence specific runtime reconfigurable processor from the ground up using a technique called "hardware & software co-exploration". Targeting advanced computer vision applications first, using proprietary hardware and software IP on existing processors like FPGAs and custom designed ASIC, the company is geared towards positively disrupting the rapidly growing AI hardware space across defense, aerospace, smart cities, industry 4.0, autonomous vehicles and robotics

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