Compiler Software Engineer 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 TM 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, Computer Engineering and/or Computer Science and/or Electrical Engineering
Experience in writing production-quality C++ code
Experience with programming in Python
Hands-on experience with code generation implementation/optimization leveraging
compiler frameworks such as LLVM, or machine learning compilers such as TVM, Glow, XLA or TensorFlow lite.
Preferred Qualifications
Strong object-oriented design and development skills.
Knowledge of neural networks, with hands-on experience using ML frameworks such
as TensorFlow or PyTorch
Experience with TDD development solutions like Google etc.
Experience with Source Code and Configuration management tools, such as Git
Strong debugging and analysis skills, for root causing complex issues
Knowledge of Convolutional Neural Networks (CNNs), RNN/LSTMs
Familiarity with any of the deep learning compiler frameworks TVM, Glow or XLA
Experience in solving large-scale combinatorial optimization problems or scheduling
algorithms
Experience developing embedded software, preferably on-device ML
