What will your job look like? Design and implement large-scale C++ systems around AI and algorithmic pipelines for 3D sensing and perception in a real-time, vehicle-oriented environment. Integrate neural network models into production software — including model runtime integration, sensor/data flow, pre/post-processing, and system-level validation — for tasks such as 3D reconstruction, object detection, and localization. Work closely with deep learning, computer vision, and 3D algorithm teams to take models from research/prototype stage into robust production systems on the vehicle. Build and own application-level infrastructure that enables algorithmic and neural network solutions to run efficiently on edge devices under strict latency and resource constraints. Optimize runtime performance, memory usage, latency, and throughput for high-precision 3D perception workloads in resource-constrained environments. Contribute to neural network deployment flows, such as ONNX Runtime integration, model conversion, inference execution, profiling, and optimization. Lead end-to-end development of features — from design and implementation to integration, testing, and deployment. Take part in building CI/CD processes, automated testing, and development workflows for production algorithm systems. Debug complex real-time systems involving C++ infrastructure, 3D algorithmic logic, and neural network execution. Collaborate with multiple teams across Mobileye, gaining deep exposure to both system architecture and state-of-the-art 3D sensing and AI algorithms. Gradually take broader technical ownership, mentor others, and grow into a technical leadership or small team leadership role. All you need is: B.Sc. in Computer Science, Software Engineering, or equivalent. 5+ years of hands-on C++ development experience. Strong understanding of object-oriented design, software architecture, and large-scale system development. Experience working in Linux environments. Strong motivation to work close to deep learning algorithms and production AI systems for autonomous vehicle 3D sensing. Interest in neural network deployment on edge devices, including inference runtimes, performance optimization, and model integration. A proactive, ownership-driven mindset, with interest in growing into a broader technical leadership role. Advantages: Experience with performance optimization, memory efficiency, and real-time systems. Experience with ONNX Runtime, TensorRT, or similar inference runtimes. Familiarity with CI/CD processes and automated testing. Experience working closely with algorithm, computer vision, deep learning, 3D perception, or data teams. Background in 3D computer vision, multi-view geometry, point clouds / depth, object detection, localization, or embedded/edge AI deployment. Experience with sensor fusion or camera/lidar-based perception pipelines (nice to have).
