Machine learning • pully vd
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We are investigating real-time edge computing architectures to enhance visual feedback in next-generation medical robotics. Our systems combine high-bandwidth video streams with real-time robotic telemetry to support precision tasks.
In this internship, you will lead the hands-on prototyping of an edge AI processing unit using a state-of-the-art Edge AI development platform. You will be responsible for bringing up the hardware from scratch, establishing a low-latency video pass-through pipeline, and evaluating how computer vision and machine learning models can extract insights and render helpful visual cues in real time.
Tasks:
• Hardware Bring-Up: Set up, configure, and benchmark a new edge AI development platform (operating system, drivers, hardware acceleration libraries, and high-speed video capture interfaces).
• Low-Latency Video Pipeline: Explore and prototype low-latency video streaming architectures using real-time processing frameworks to capture high-resolution camera feeds and drive responsive external displays.
• Telemetry & Visual Overlays: Ingest robotic telemetry alongside the video feed to render dynamic graphical annotations and spatial guidance cues directly onto the live stream.
• Computer Vision & AI Prototyping: Benchmark lightweight computer vision algorithms and modern neural network architectures (e.g., for object tracking, state awareness, or semantic scene understanding) on edge hardware.
• System Profiling & Documentation: Measure end-to-end processing delays, evaluate hardware resource utilization, and document the architecture to guide future product development.
Requirements
Required abilities:
• Enrolled in a Master’s degree or final year of a Bachelor’s program in Computer Science, Robotics, Embedded Systems, Electrical Engineering, or a related discipline.
• Practical programming experience in Python or C++.
• Working knowledge of Linux environments, shell scripting, and version control (Git).
• Foundational understanding of computer vision or machine learning using standard libraries (such as OpenCV, PyTorch, or ONNX Runtime).
• An exploratory, hands-on mindset with an interest in hardware bring-up, lab prototyping, and embedded development.
• Open-minded, self-driven & creative problem solving
• Fluency in English is a must
Beneficial Experience:
• Familiarity with real-time streaming SDKs (e.g., NVIDIA Holoscan, DeepStream, or GStreamer) or GPU acceleration tools (CUDA, TensorRT).
• Basic understanding of sensor fusion or 2D/3D coordinate transformations.
Benefits
What we offer:
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