GPGPU Software Engineer
Confirmed live in the last 24 hours
High-efficiency AI system for autonomous vehicles
Company Overview
Recogni stands out in the automobile industry with its unique approach to designing a vision-oriented inference artificial intelligence system, delivering an unprecedented 500x better power efficiency compared to other solutions. This enables edge processing at multiple points on vehicles, reducing the need for central processing and accelerating the development of fully-autonomous vehicles. The company's strong foundation in high-performance computing, artificial intelligence, machine learning, and imaging and vision systems, coupled with its commitment to user privacy and data security, make it a promising place to work and grow.
AI & Machine Learning
Automotive & Transportation
Company Stage
Series B
Total Funding
$73.9M
Founded
2017
Headquarters
San Jose, California
Growth & Insights
Headcount
6 month growth
↑ 13%1 year growth
↑ 16%2 year growth
↑ 60%Locations
San Jose, CA, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Computer Networking
OpenGL
CategoriesNew
Software Engineering
Requirements
- B.S. (M.S. preferred) in Computer Science, Electrical or Computer Engineering or a related field
- 3+ years of experience developing embedded software
- C/C++ fluency / OpenGL/GLSL fluency
- Object-oriented programming / API design experience
- Debugging / profiling / optimizing experience
- Experience with full life-cycle of development, including product release
- Innovative mindset
- Highly motivated and eager to learn
- Strong communication and problem-solving skills
- Experience with cross-platform / large scale software development
- Experience with GUI libraries, specifically Qt
- Experience with Operating System Kernels and multi-threaded programming
- Knowledge of computer networking
- TVM
- Halide etc
- LLVM
- CDNN (Ceva Deep neural Network)
Responsibilities
- As a member of Recogni's embedded software team, you will be responsible for implementing the software that runs inside a high-performance and low-power convolutional neural network accelerator ASIC that forms the core of the company's flagship perception module product for autonomous driving applications