Senior C++ Developer – Neural Network Integration & Production AI Systems

What will your job look like?

• Design and implement large-scale C++ systems around AI and algorithmic pipelines in a real-time-oriented environment.
• Integrate neural network models into production software, including model runtime integration, data flow, pre/post-processing, and system-level validation.
• Work closely with deep learning and computer vision algorithm teams to take models from research/prototype stage into robust production systems.
• Build and own application-level infrastructure that enables algorithmic and neural network solutions to run efficiently on edge devices.
• Optimize runtime performance, memory usage, latency, and throughput 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, algorithmic logic, and neural network execution.
• Collaborate with multiple teams across Mobileye, gaining deep exposure to both system architecture and state-of-the-art 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.
• 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.
• 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, or data teams.
• Background in computer vision, deep learning systems, or embedded/edge AI deployment.