Senior Embedded Software Engineer

Faraday Future (FF) is a California-based mobility company, leveraging the latest technologies and world’s best talent to realize exciting new possibilities in mobility. We’re producing user-centric, technology-first vehicles to establish new paradigms in human-vehicle interaction. We’re not just seeking to change how our cars work – we’re seeking to change the way we drive. At FF, we’re creating something new, something connected, and something with a true global impact.

We are seeking a highly skilled Senior Embedded Software Engineer to join our ADAS platform development team. The ideal candidate will have proven experience in designing, implementing, and optimizing embedded frameworks for advanced driver-assistance systems (ADAS) on platforms such as NVIDIA Orin/Thor or Qualcomm 8797. The engineer will play a key role in developing and integrating ADAS frameworks with vehicle systems, evaluating and enhancing platform capabilities, while also ensuring seamless integration of sensor inputs and vehicle control outputs. Familiarity with open-source ADAS stack, ML/AI model optimization, and cross-platform inference engines is highly preferred. 

Responsibilities: 

• Requirements Analysis & Specification 
  • Analyze ADAS platform requirements and define technical specifications for system-level framework development. 
  • Evaluate platform-level capabilities such as task scheduling, inter-process communication, log/data management, OTA, and diagnostics to meet safety and performance needs 
• Software Design & Development 
  • Design and implement ADAS framework components on NVIDIA Orin/Thor or Qualcomm-based platforms, such as task scheduling, messaging, logging, OTA, diagnostics and Health. 
  • Develop middleware and integration layers to support sensors (cameras, radars, LiDARs) and control output to vehicle actuators (braking, steering, acceleration) over CAN/LIN/Ethernet. 
  • Integrate open-source ADAS stacks into automotive-grade systems, ensuring compatibility with platform-specific hardware and software ecosystems, and optimize inference on CUDA or SNPE toolchains. 
• Maintenance & Optimization 
  • Optimize platform performance for stability, latency, and reliability. 
  • Enhance ADAS frameworks to support scalability, maintainability, and efficient debugging. 
• Testing & Validation 
  • Conduct integration testing of ADAS framework components with perception modules, decision-making units, and vehicle actuators. 
  • Perform platform stress testing and ensure compliance with automotive safety and reliability standards. 
• Cross-Functional Collaboration 
  • Work closely with hardware, systems, and vehicle integration/test engineers to ensure robust end-to-end performance. 
  • Engage with external vendors and partners for toolchain, platform, and sensor integration. 
• Documentation & Configuration 
  • Document system architecture, design decisions, and integration procedures. 
  • Maintain configuration management for multi-platform builds and continuous integration process.  

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Software Engineering, or a closely related field. 
• 7+ years of Linux-based embedded software development experience in automotive or related domains. 
• Proven experience with ADAS frameworks on NVIDIA Orin/Thor, Qualcomm 8797, or similar high-performance embedded platforms. 
• Hands-on experience with sensor integration (cameras, radars, LiDARs) and control outputs via CAN/LIN/Ethernet. 
• Experience in ML/AI model optimization and inference deployment using ONNX(or other deep learning models), CUDA, TensorRT, or SNPE. 
• Strong programming skills in C/C++ and Python for embedded Linux System development. 
• Deep knowledge of embedded Linux/RTOS, inter-process communication, scheduling, and memory management. 
• Experience in OTA updates, diagnostics, and system performance optimization. 
• Familiarity with diagnostic standards and protocols, such as UDS over IP or CAN. 
• Solid understanding of log management, data pipelines, and real-time debugging tools. 
• Strong problem-solving and cross-functional communication skills. 

• Proven experience integrating open-source ADAS/AV stacks, with knowledge of its module architecture (perception, planning, control) and adaptation to proprietary hardware.
• Familiarity with simulation tools and HIL testing environments for ADAS validation. 
• Knowledge of machine learning deployment in ADAS pipelines (e.g., TensorRT for Nvidia, Hexagon DSP for Qualcomm). 
• Experience with Vector tools (CANoe, CANalyzer) for validating ADAS-related features.

($135,000 - $155,000 DOE), plus benefits and incentive plans