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We are seeking a Software Engineer to join our Physical AI team, focused on building next-generation platforms for automotive and robotics applications. This role operates at the intersection of embedded systems, high-performance computing, AI, and robotics, offering the opportunity to contribute across the full hardware and software stack. You will play a key role in supporting the development and integration of the RAVE2 platform, ensuring that technical information is clearly documented and communicated to both internal and external stakeholders. As the team and platform evolve, you will have the opportunity to expand into areas such as embedded AI inference, computer vision pipelines, robotics software, graphics technologies, and simulation environments used to develop intelligent systems. You will work closely with multidisciplinary engineering teams across hardware, FPGA, AI, and software engineering in a collaborative and innovation-driven environment, helping to bring cutting-edge Physical AI solutions into real-world applications.
Job Responsibility
Contribute to the development, integration, and support of embedded Linux platforms
Support the bring-up, debugging, validation, and optimisation of embedded systems
Develop and maintain high-quality technical documentation for the RAVE2 platform
Collaborate with cross-functional teams across hardware, FPGA, AI, and software domains
Investigate and resolve software, hardware, and system-level challenges
Contribute to system design, performance analysis, and validation activities
Help define and improve engineering best practices and development processes
Establish strong familiarity with the RAVE2 platform and documentation standards
Contribute to platform bring-up, integration, and system validation efforts
Begin supporting broader development areas such as AI inference, vision, or robotics pipelines.
Requirements
Experience in software development using C/C++ and/or Python
Strong familiarity with Linux operating systems and development environments
Understanding of embedded systems architecture and hardware/software interactions
Experience debugging complex system-level issues
Exposure to multidisciplinary engineering environments.
Nice to have
Experience with FPGA-based systems or hardware acceleration
Knowledge of SoCs and ASIC-based platforms
Familiarity with RTOS or automotive software architectures such as AUTOSAR
Experience with graphics stacks (e.g., OpenGL, Vulkan, Wayland)
Exposure to ROS 2, robotics middleware, or sensor integration
Experience with simulation environments (e.g., Gazebo, Isaac Sim, CARLA)
Understanding of AI inference deployment and computer vision pipelines
Industry exposure to automotive, robotics, or autonomous systems.