Edge AI & Computer Vision Intern

Distalmotion SA

Epalinges, Switzerland
Internship
Intern/New Grad
Bachelor's degree
Posted 4 Nov 2026

Skills

Required

computer vision / machine learning
Robotics
hardware bring-up
Embedded Systems
Python / C++
Linux environments
shell scripting
version control
Git
OpenCV / PyTorch / ONNX
Runtime
lab prototyping

Preferred

AI
real-time
streaming SDKs
NVIDIA
Holoscan / DeepStream / GStreamer
GPU acceleration tools
CUDA
TensorRT
sensor fusion / 2D/3D coordinate transformations
Prototyping

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.

About Distalmotion SA

A dynamic, innovative environment with cutting-edge medical technology that is shaping the future of robotic surgery.

Responsibilities

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

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

Preferred

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

Fast-growing Company where innovation meets agility.
Structured onboarding program and training, ensuring a confident start.
High degree of autonomy and flexibility.