Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
API @ 4
CUDA @ 4
Communication @ 6
Debugging @ 7
Git @ 4
Linux @ 7
Matlab @ 4
OpenCL @ 4
OpenGL
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Responsibilities
- Designing and developing core components of NVIDIA DriveWorks SDK.
- Developing and optimizing software architecture and frameworks for real-world performance while matching or exceeding customer requirements.
- Working on areas such as sensor abstraction layers, data processing components, process scheduling, data serialization, network communications, and frameworks.
- Performing in-vehicle tests, collecting data and completing autonomous drive missions.
- Establishing unit tests, documentation for features, evaluating quality and proposing corrective actions.
- Developing highly efficient production code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA). Follow quality and safety standards such as defined by MISRA and AUTOSAR.
Requirements
- BS or MS in Computer Engineering, Computer Science, or related engineering field (or equivalent experience).
- 5+ years of professional experience working on autonomous vehicles software.
- Excellent C and C++ programming skills.
- Strong knowledge of programming and debugging techniques, especially for parallel and distributed architectures.
- Proficient with AI-powered coding tools like Cursor, Copilot, Gemini, etc.
- Strong background of Linux, QNX, and/or other real-time operating systems.
- Thrive on writing low latency, highly performant code.
- Great communication and analytical skills.
Ways to Stand Out From the Crowd
- Experience with data-parallel and/or GPGPU programming, CUDA, OpenCL.
- Knowledge of image processing APIs (e.g. OpenCV) and MATLAB tools.
- Knowledge of automotive systems, notably ADAS applications.
- Software development for modern OpenGL (Core Profile) and Linux.
- Experience with version control systems GIT and build system Bazel.
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