Job Description
Job description
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.,
