Software Engineer/senior Software Engineer, Video Analytics, Gec

2 months ago


Paya Lebar Singapore ST Engineering Full time

Position: C++ Software Engineer - Computer Vision Specialist

Responsibilities: * Collaborate with the software development team to design, implement, and optimise video analytics models using C++.
  • Integrate video analytics models seamlessly into our existing software infrastructure.
  • Work closely with cross-functional teams to understand project requirements and ensure successful deployment of video analytics solutions.
  • Optimise video analytics algorithms for enhanced performance on both CPU and GPU platforms.
  • Conduct thorough testing and debugging of integrated solutions to ensure reliability and accuracy.
  • Stay abreast of industry trends, emerging technologies, and advancements in video analytics to contribute to the evolution of our products.
  • Collaborate with hardware engineers to ensure proper integration and utilisation of hardware acceleration technologies. Qualifications: * Bachelor\'s or Master\'s degree in Computer Science, Engineering, or a related field.
    • Proven experience as a C++ Developer with a focus on video analytics.
    • Strong understanding of video analytics algorithms and models.
    • Proficient in optimising and fine-tuning video analytics models for performance improvement.
    • Excellent problem-solving skills and attention to detail.
    • Effective communication and collaboration skills.
    • Able to work independently or in a team.
    • Willing to work in Paya Lebar but can travel to various parts of Singapore if needed.
    • Singaporean only
    • Fresh graduates are welcome to apply and successful candidates with relevant experience may be considered for senior position. Preferred Qualifications: * Prior experience in integrating video analytics solutions into real-world applications.
      • Familiarity with edge computing and deployment of video analytics models on edge devices.
      • Knowledge of other relevant technologies, frameworks, and libraries in the video analytics ecosystem.
      • Familiarity with neural network frameworks like TensorRT, TensorFlow or PyTorch.
      • Hands-on experience with Nvidia\'s technology stack, including Nvidia DeepStream, will be an advantage.
      • Experience with GPU programming and parallel computing will be an advantage.
      • Experience in optimising and adapting models for resource-constrained environments.

        ST Engineering



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