Computer Vision & Hardware Engineer
Indexed description
We are setting up a global R&D centre with a state-of-the-art applied AI laboratory, equipped with NVIDIA edge platforms (Jetson / RTX), industrial global-shutter cameras, precision lenses, strobed lighting systems, and high-performance GPU workstations. Engineers will work hands-on with real production hardware, building and optimizing AI systems deployed directly on manufacturing lines.
Key Responsibilities
- Design, develop, and optimize computer vision algorithms for real-time applications in manufacturing processes
- Implement GPU-accelerated solutions using frameworks like CUDA and OpenCL for enhanced performance
- Collaborate with cross-functional teams to integrate vision systems with hardware and cloud services
- Conduct performance profiling, benchmarking, and implementation of optimizations for image processing tasks
- Research and apply the latest advancements in computer vision, image processing, and deep learning
- Support model training and deployment on edge devices and cloud environments
- Troubleshoot and debug hardware and software issues related to vision systems
- Maintain comprehensive documentation of algorithms, architectures, and workflows
- Mentor junior engineers as needed and contribute to a collaborative team environment
- Participate in Agile development practices, including sprint planning and retrospectives
- Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related fields
- 3+ years of experience in computer vision and image processing, with a focus on real-time applications
- Proficient in programming languages such as Python and C/C++; experience with embedded programming is a plus
- Strong expertise in GPU programming using CUDA and/or OpenCL
- Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch
- Solid understanding of key computer vision techniques including image segmentation, object detection, and tracking
- Familiarity with edge computing and deployment frameworks for AI models
- Experience with version control systems, particularly Git
- Strong analytical skills and problem-solving abilities, with attention to detail
- Excellent communication skills for collaboration within a team environment
- Knowledge of industrial automation and IoT systems is a plus
- Private Health Insurance
- Paid Time Off
- Training & Development
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