Drive innovation by developing sophisticated custom software solutions. This role involves designing, coding, and enhancing system components, leveraging modern frameworks and agile methodologies to deliver scalable, high-performance applications tailored to unique business requirements. Embrace best practices in software engineering to build robust and efficient solutions.

This position offers an exciting opportunity to work with cutting-edge technologies, including AI/ML and GenAI, to enhance automotive systems. You will be instrumental in integrating advanced features and ensuring compliance with stringent industry standards. Join a dynamic team focused on shaping the future of automotive software.

Support the development of Software for ADAS Projects, ensuring strict compliance with ISO 26262, ASPICE, and cybersecurity standards. Collaborate effectively with OEMs, Tier-1 suppliers, and internal teams to align technical and programming objectives. Facilitate the development of cloud-based vehicle data platforms and V2X communication strategies. Integrate AI/ML for perception and decision-making, utilizing GenAI for code generation, test automation, and documentation. Leverage GenAI tools for requirements analysis, defect prediction, test case generation, and engineering knowledge reuse.

A minimum of 3 years of experience in Automotive ECU Software is essential. Candidates should possess a Bachelor's or Master's degree in Electrical Engineering, Computer Science, or Automotive Engineering. Strong proficiency in embedded systems, real-time software, and automotive communication protocols like CAN, LIN, and Ethernet is required. Experience with RTOS, ADTF, AUTOSAR, and NVIDIA DRIVE SDK is highly beneficial. Familiarity with ISO 26262, ASPICE, and ISO/SAE 21434 standards, along with experience in cloud connectivity and V2X communication, is expected. Exposure to global automotive markets and regulatory environments is advantageous. Hands-on experience with NVIDIA Omniverse, Isaac Sim, and GenAI engineering tools is a plus. Knowledge of model-based development and simulation frameworks, along with specific experience in ADAS & Autonomous Systems (e.g., lane keeping, adaptive cruise, collision avoidance) and vehicle architectures, is preferred.