Machine Learning Video Analytics Expert

7 days ago


Singapore ST Engineering Full time

About Us


ST Engineering Land Systems Ltd is a leading provider of training solutions to the Military and Commercial sectors.


We are seeking an experienced Machine Learning Engineer to join our team in Singapore. The ideal candidate will have a strong background in deep learning and computer vision, with experience in developing production quality video analytics software.


Job Description


We offer a challenging and rewarding role that involves working on end-to-end projects, from research and development to deployment and maintenance.


You will be responsible for designing and implementing deep learning models to tackle real-world video analytics problems, as well as translating state-of-the-art techniques into working products.


In addition to your technical skills, you should possess excellent problem-solving and analytical skills, with good communication and teamwork abilities.


Requirements



  • Experience with deep learning frameworks such as TensorFlow, Keras, PyTorch, Caffe2, and MXNet for computer vision tasks.
  • Proficiency in mainstream programming languages, including C/C++, Python, JavaScript, PHP, etc.
  • Familiarity with MLOps platforms such as MLFlow, KubeFlow, AWS Sagemaker, Azure ML, etc.
  • Knowledge of specific libraries for image processing, encryption, OpenCV, OpenSSL, PCL, etc.
  • Ability to work independently with minimum guidance and monitoring, with good teamwork skills.
  • Able to solve complex problems and think critically, with a strong attention to detail.
  • An explorative personality with a hunger for continuous improvements and professional growth.

About the Role


This role offers a competitive salary package of SGD 120,000 - SGD 180,000 per annum, depending on experience.


The location is ST Engineering Land Systems Ltd, Jalan Boon Lay, Singapore.


This job offers a chance to work on cutting-edge technology and contribute to the growth and expansion of our product development team.



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