Lead Software Engineer, Recogni
Office located in San Jose, CA
Vision-oriented AI platform for autonomous vehicles
Job no longer available
Vision-oriented AI platform for autonomous vehicles
21-100 employees
Job no longer available
Office located in San Jose, CA
21-100 employees
Company mission
To provide the highest-performing AI-based visual inference for autonomous vehicles.
Role
Who you are
- B.S. (M.S. preferred) in Computer Science, Electrical or Computer Engineering or a related field
- 10+ years of experience developing software
- Excellent proficiency in C/C++ programming coupled with a genuine passion for software development
- Experience with low-level RTOSes (QNX, vxWorks, ThreadX, etc.) and developing device drivers for them
- Experience with embedded development IDEs and debuggers (gdb, lldb, etc.) and JTAG-based debugging
- Experience with embedded development tool-chains and cross-compilation methodologies
- Experience with multiprocessor-based embedded systems
- Experience with software architecture, development and testing best practices
- Experience with automated software testing systems for embedded systems
- Experience with with standard hardware blocks and protocols (MIPI, PCIe, USB, GPIO, I2C, SPI, UART, MMU, DMA, etc.)
- Some experience working with safety critical systems with exposure to DO-178C or ISO 26262 preferred, but is not a must
- Demonstrable proficiency with test equipment relevant to embedded product development (JTAG, logic analyzers, scopes, etc.)
- Ability to comprehend hardware specs and schematics
- Familiarity with version control systems (expertise in Git is strongly-preferred)
- Self-starter and highly-motivated to work in a dynamic start-up environment
What the job involves
- Work as a principal technical contributor in the definition, design, implementation and verification of the embedded software of a high-performance AI-based camera and perception module for ADAS systems
- Utilize formal design processes to develop embedded software that meets the high-reliability and functional safety requirements of the the perception module
- Contribute to the selection, integration and debug of real-time operating systems (RTOS)
- Integrate (or develop where necessary) low-level I/O drivers (e.g. Automotive Ethernet, USB, GPIO, etc.)
- Implement cryptographic integrity checking, secure boot (with hard time-to-operational requirements) and over-the-air update lifecycle functionalities for the embedded software
- Collaborate with hardware engineers designing application-specific integrated circuits (ASIC) in the selection of embedded CPU cores (e.g. ARM, RISC-V, etc.), as well as supporting functionality variants of those cores (e.g. MMU, MPU, VLIW vector units, etc.)
- Perform system bringup, debugging and testing
- Perform requirements analysis and author high-level and detailed requirements
- Troubleshoot software issues and fix defects
- Write test specifications and integration tests
- Architect and maintain automated software build flows, integrate with continuous integration (CI) systems, and author scripts and utilities
Our take
With an investor list including the likes of Toyota, BMW and Continental, it’s perhaps safe to say that Recogni is already a contender in its sector. Its visual perception platform has been created specifically for autonomous vehicular use, from safety feature development to full self-driving vehicles. Using AI neural network accelerator technology utilising high-res imagery, HDR stereo sensing, and analysing data in real time.
Recogni saw an opportunity when they assessed the market of visual perception products and found that systems were either high performance platforms with a huge power drain, or low power, economical alternatives that compromised on performance. Recogni’s goal was to create a platform that is both powerful and economical.
Impressive investment in the company is being used to manufacture and market Recogni's new slate of AI chips, which are more specified than the current large language model training chips on the markets. Recogni's chips stand out because they focus on "inference" in the AI training process, allowing its models to make predictions based on new data - an integral part of the self-driving vehicle system. More efficient than current chips on the market, Recogni is well on its way to securing its seat in the autonomous vehicle development sector.
Freddie
Company Specialist at Welcome to the Jungle
Insights
6% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Feb 2024
$102m
SERIES C
Feb 2021
$48.9m
SERIES B
Total funding: $175.9m
Company benefits
- Learning and development opportunities
- Employee stock purchase plan
- 401K
- Dental, vision and life insurance
- Flexible work hours
- Generous PTO policy
- Work from home opportunities
- Health insurance
Company HQ
North San Jose, San Jose, CA
Leadership
Gilles Backhus
(VP of AI)Gilles has an extensive background in realtime AI development having lead and founded multiple AI based companies.
R K Anand
(CPO)R K comes from a Computer Engineering background and has gained extensive experience in managing and founding multiple technology enterprises.
Valerie Chan
(VP of Global Operations)Valerie is an experienced entrepreneur and executive with a demonstrated history of success in the hardware/technology/internet industries.
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