Research Scientist

2 days ago

Perth, Western Australia beBeeArtificialintelligence Full time $155,000 - $175,000
AI Researcher - Traffic Engineering and Safety Analysis

We are seeking an experienced AI researcher to join our team in developing innovative solutions for traffic engineering and safety analysis. This role combines applied AI research with real-world applications, offering the opportunity to work on impactful projects at the intersection of cutting-edge technology and transportation safety.

  • Key Responsibilities:
  • Investigate, benchmark, and optimize model architectures for detection, segmentation, and tracking in complex transport environments.
  • Enhance multi-object tracking pipelines using advanced methods such as DeepSORT, ByteTrack, and Transformer-based approaches.
  • Improve video analytics performance through evaluation of alternative models and pipeline optimization.
  • Develop post-processing logic for trajectory denoising, smoothing, and error reduction.
  • Apply denoising techniques to improve low-resolution or low-bitrate footage.
  • Conduct field validation of model performance across diverse environments and camera types.
  • Support camera calibration workflows for accurate spatial measurements.
  • Run ablation studies and model evaluations under varied environmental conditions.
  • Collaborate with cloud engineering teams for scalable inference deployment using ONNX, TensorRT, Triton, or similar.
  • Translate AI outputs into transport safety and engineering metrics.

The ideal candidate will have a PhD in Computer Science, Applied Mathematics, Robotics, Physics, or related discipline, or equivalent experience with a strong applied AI/computer vision track record. Expertise in object detection, segmentation, and multi-object tracking in complex scenarios is essential, along with proficiency in deep learning frameworks (PyTorch, TensorFlow) and Python libraries (OpenCV, Yolo, NumPy, scikit-learn).

Required Skills and Qualifications:
  • PhD in Computer Science, Applied Mathematics, Robotics, Physics, or related discipline; or equivalent experience with a strong applied AI/computer vision track record.
  • Expertise in object detection, segmentation, and multi-object tracking in complex scenarios.
  • Proficiency with deep learning frameworks (PyTorch, TensorFlow) and Python libraries (OpenCV, Yolo, NumPy, scikit-learn).
  • Proven experience in real-world video analytics and model deployment under challenging conditions.
  • Experience with model optimization and inference acceleration.
  • Familiarity with denoising techniques for low-quality video.
  • Understanding of camera calibration and spatial measurement.
  • Strong communication skills and ability to work independently and in multi-disciplinary teams.
  • GPU-based inference deployment (ONNX, TensorRT, Triton).
  • Knowledge of transport/traffic datasets.
  • Track record of publications or open-source contributions.
  • MLOps tools and practices (MLflow, Weights & Biases).
  • Experience with Transformer architectures for video data.

This is an exciting opportunity to contribute to the development of innovative solutions for traffic engineering and safety analysis. If you have a passion for AI research and a drive to make a real impact, we encourage you to apply.

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