Computer Vision Engineer

Location Singapore
Discipline Information & Communications Technology
Job Reference BBBH139653_1720425863
Salary Up to S$0.00 per annum
Consultant Name Goel Navneet
Consultant Email [email protected]
Consultant Contact No. 65515581
EA License No. 02C3423
Consultant Registration No. R1982194


  • End-to-End Project Ownership: Take comprehensive responsibility for development of computer vision pipelines, from initial concept to deployment including ideating, building and refining the solutions.
  • High-Performance Pipelines: Spearhead the development of robust and scalable computer vision pipelines focusing on both local and cloud-based applications.
  • Benchmarking and Working with State-of-the-Art Models: Engage in thorough benchmarking activities to assess and enhance the accuracy of latest computer vision breakthroughs. Strive for optimization and latest advancements in the field.
  • Bug Fixing: Proactively identify and resolve software bugs, ensuring the deployment process is smooth and efficient.
  • Cross-Team Collaboration for Solution Development: Engage in close collaboration with various stakeholders, including subject matter experts, to develop comprehensive solutions.

Technical Abilities

  • Bachelor's or master's in computer science, Electrical Engineering, or related field, or equivalent experience.
  • Over 3 years of experience working with Computer Vision, especially in training models and developing efficient pipelines, with a focus on object detection, image segmentation, and pose estimation.
  • Proficiency with Python, image processing libraries like OpenCV and Pillow and deep learning frameworks like PyTorch and TensorFlow.
  • Demonstrated expertise in developing and implementing computer vision pipelines, understanding visual data processing and algorithms.
  • Solid understanding of data structures, algorithms, and software design principles.
  • Experience in model optimization, including edge hardware deployment. Experience with Deepstream/GStreamer/Edge optimised libraries is a plus.
  • Research experience or working experience with loT/Edge devices .
  • Demonstrated ability to produce highly scalable pipelines, working effectively both independently and as part of a team.
  • Excellent communication abilities to articulate findings and technical challenges to both technical and non-technical stakeholders.