Senior Software Engineer - Perception & Sensor Fusion (Deep Learning)

Responsibilities

1. Develop perception algorithms for object detection, tracking, classification, and segmentation using deep learning.
2. Design and maintain multi-sensor fusion pipelines (LiDAR, camera, GPS/IMU, Radar) time synchronization, calibration, and coordinate-frame transforms.
3. Train, validate, and fine-tune AI/ML models to meet performance, accuracy, and reliability requirements
4. Develop algorithms and optimise for LiDAR and Camera sensor data processing, including tracking filters (e.g., Kalman filters, particle filters), feature extraction, object detection, and sensor fusion techniques
5. Integrate trained models into the production system, ensuring smooth deployment and operation under production-grade ROS (1/2) nodes in C++.
6. Take models from research to deployment - TensorRT conversion, quantization, and latency/throughput optimization on NVIDIA embedded platforms.
7. Build and maintain offline replay/validation tooling against recorded sensor data.
8. Collaborate with cross-functional teams (data engineering, software, hardware) to ensure end-to-end system integration
9. Maintain documentation of AI models, pipelines, and integration processes for maintainability and scalability
10. Stay updated on relevant AI/ML advancements and recommend improvements to existing systems

Requirements

1. Degree, Master's or PhD in Computer Science, Engineering, or a related field (or equivalent industry experience).
2. Strong C/C++ and object-oriented design skills on Linux, plus Python for tooling.
3. Working knowledge of LiDAR/camera geometry: calibration, projection, plane fitting, point-cloud registration.
4. ROS (1 and 2) experience.
5. 3+ years with a deep-learning stack such as OpenCV, TensorFlow, Tensor RT, PyTorch, or Caffe.
6. 5+ years of Linux system development.
7. 3+ years on robotic/autonomous/ADAS systems, with Camera and/or LiDAR and/or Radar development.
8. Proficient with Git, Docker, and CI/CD pipelines.
9. Self-motivated, able to own ambiguous problems end-to-end with minimal supervision.

Nice to have

1.  Experience with foundation/promptable segmentation models.
2.  Experience with Open3D, PCL, or similar point-cloud libraries.
3.  Experience with geospatial/GIS data (GPS alignment, routing APIs).
4.  Experience building 3D reconstructions or maps from sensor data.