What You'll Do
Design and implement embedded C/C++ software for a high-performance ADAS compute platform. You'll ensure software operates efficiently across multiple System-on-Chip architectures, including arm64 and x86, and functions reliably on operating systems such as Linux and QNX.
Lead integration efforts for both system-level and software components, connecting ADAS sensors and compute units. You'll also integrate machine learning models and core ADAS algorithms into the platform, ensuring compatibility and performance.
Support end-to-end vehicle integration and validation processes, working closely with cross-functional teams to verify functionality and reliability in real-world conditions.
Requirements
- Minimum of 10 years in software engineering
- Degree in Computer Science or a related discipline
- Strong expertise in C++ (C++11 and later) and Linux environments
- Proficiency with C++ design patterns, especially concurrency models
- Proven experience integrating machine learning models on SoC-based hardware accelerators
- Hands-on experience with ROS or ROS2, particularly ROS2 Humble
- Background in real-time, multi-threaded, and multi-process software development
- Experience with camera image pipelines, ISP configuration, and tuning
- Skill with cross-platform build systems such as CMake
- Track record integrating third-party open-source software and cross-compiling for embedded targets
- Solid understanding of SoC architectures and high-performance computing software stacks
- Detailed knowledge of ADAS sensors including cameras, radar, ultrasonic, and lidar
- Familiarity with hardware accelerators like ISP, GPU, and NPU
- Working knowledge of GNSS, V2X, and MAP/ADASIS systems
- Understanding of high-speed interfaces including GMSL, FPD-Link, and MIPI CSI/DSI
- Proficiency with communication protocols such as Ethernet, UART, CAN, USB, I2C, and SPI
Preferred Qualifications
- Experience with Python, QNX, or Adaptive AUTOSAR
- Background using Docker containers in development workflows
- Familiarity with computer vision algorithms
- Understanding of automotive safety and security principles
- Experience with debugging tools such as Lauterbach
Benefits
- Flexible working hours and remote work options
- Health and wellness initiatives, sports, and team-building activities
- Comprehensive training and internal career development
- Meal allowance provided
