AI + Autonomous Driving Software Engineer

Role Overview: As an AI + Autonomous Driving Software Engineer in Ahmedabad, you will be responsible for leading the implementation and customization of open-source autonomous-driving frameworks such as Autoware, Apollo, and CARLA. Your primary focus will be on building lane/path detection, path planning, and vehicle-control capabilities for the platform. Your tasks will involve integrating perception models, tuning planning algorithms, optimizing performance on embedded hardware, and preparing the system for on-road deployment. Key Responsibilities: - Integrate and extend open-source autonomous-driving stacks (Autoware or Apollo) for real-time perception, mapping, planning, and control. - Implement lane/path detection using classical CV and deep-learning models; adapt and optimize neural-network perception pipelines. - Develop, tune, and test path-planning algorithms including local planners, behavior planners, and trajectory generators. - Build simulation pipelines using CARLA or similar tools to validate perception and planning modules. - Customize modules to meet hardware-specific constraints such as sensors, compute platforms, and CAN interfaces. - Create tools for logging, visualization, and debugging of autonomous-driving behavior. - Collaborate with mechanical, sensor, and platform teams to ensure robust integration on physical vehicles. - Contribute to safety, testing, and performance-validation frameworks. Qualifications Required: - Strong proficiency in C++ and Python. - Experience with ROS/ROS2, Autoware, or Apollo. - Hands-on experience with computer vision and deep learning tools such as OpenCV, PyTorch, or TensorFlow. - Understanding of sensor fusion, SLAM, mapping, tracking, or localization pipelines. - Familiarity with path planning algorithms like A*, RRT, MPC, PID, motion control, and trajectory optimization. - Experience with simulation tools like CARLA, Gazebo, and data-logging workflows. - Ability to work with LiDAR, radar, camera sensors, and integrate new sensor modalities. - Strong debugging, optimization, and system-integration skills. Preferred / Nice-to-Have Skills: - Experience deploying on embedded compute platforms, especially the NVIDIA Jetson family. - Background in ADAS or autonomous driving. - Experience with CAN bus/vehicle interface integration. - Knowledge of safety frameworks such as ISO 26262, SOTIF. - Understanding of reinforcement learning or end-to-end driving models.,