Engineer (Video Analytics Application and Deployment)

Responsibilities

• Gather, design and test video analytics (VA) and computer vision (CV) requirements on unmanned air systems (UAS) and their sub-systems.
• Have knowledge of VA/CV algorithms and tools.
• Deploy and configure VA/CV modules and applications according to requirements.
• Modify or develop VA/CV modules and applications when necessary.
• Train and retrain VA machine learning (ML) models when necessary.
• Maintain and update software documentation and related technical documentation.
• Liaise with vendors and sub-contractors
• Manage and train data/image annotators.
• Work with other members in Data Analytics group (DAG) to support projects.
• Develop and maintain interface control documents between ground control systems and machine learning models.
• Select, configure and install the following based on project VA/CV requirements:
  • Edge computing device
  • Workstations / servers
  • Sensors 

Requirements

• Bachelor's Degree in Computer Science or related technical discipline
• Experience in software development using C++ and/or Python
• Knowledge in deep learning frameworks such as Tensorflow, PyTorch, Mxnet, Scikit-learn, Numpy, Pandas, TensorRT, IntelOpenVino
• Strong problem solving, analytical and conceptual skills, with good communication skills
• Able to work independently with minimum guidance and monitoring, a good team player
• Able to travel overseas (short-term)
• Preferable:
  • Experience in embedded platforms (e.g. Nvidia Jetson, Intel UP Squared).
  • Experience using MLOps and ML lifecycle management platforms such as MLFlow, KubeFlow, AirFlow.
  • Experience using Docker.
  • Experience in software packaging, deployment, UAT, and production.
  • Experience in OpenCV or other computer vision packages.
  • Experience in Linux-based operating systems.