- Design and develop software for autonomous navigation, including localization, mapping, perception, path planning, obstacle avoidance, and motion decision logic.

- Build and optimize AI/ML models for object detection, classification, tracking, scene understanding, and behavior prediction.

- Develop and integrate sensor fusion solutions using data from cameras, LiDAR, radar, GPS, IMU, and other onboard sensors.

- Implement navigation and autonomy algorithms for structured and unstructured environments.

- Collaborate with systems, controls, and platform teams to integrate autonomy functions into vehicle software architecture.

- Develop software in C++ for real-time or near-real-time autonomy applications.

- Create simulation and test pipelines for model training, algorithm validation, and system verification.

- Support field testing, debug performance issues, and refine autonomy behavior based on real-world results.

- Improve software reliability, safety, performance, and maintainability using sound engineering practices.

- Contribute to requirements definition, technical planning, architecture reviews, and code reviews.

- Mentor junior engineers and provide technical leadership in AI/ML and autonomy development.

- Support transition from prototype algorithms to production-ready implementations.

Required Qualifications :

- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Aerospace Engineering, or related field.

- 7+ years of software development experience with significant work in AI/ML, robotics, autonomous systems, or navigation.

- Strong programming skills in C++.

- Knowledge of AI/LLM training and deployment.

- Experience with ML frameworks (PyTorch, TensorFlow, or equivalent).

- Experience developing perception or navigation algorithms for autonomous systems.

- Strong understanding of one or more of the following areas :

1. Sensor fusion

2. SLAM / localization / mapping

3. Path planning / trajectory generation

4. Computer vision

5. Object tracking

6. Reinforcement learning or behavior planning

- Experience with robotics middleware or autonomy frameworks such as ROS/ROS2 or equivalent.

- Experience with message bus and microservice-based architectures.

- Hands-on experience with real-world sensor data from LiDAR, radar, cameras, GPS, and IMU.

- Familiarity with simulation tools and data analysis workflows.

- Proficiency in Linux-based development environments, Git, CI/CD, and modern software engineering practices.

- Strong debugging, problem-solving, and system integration skills.

- Ability to work effectively in cross-functional teams.