Senior Computer Vision and AI Engineer Lead

Edison Smart® Germany
Remote
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AI Summary

Lead the development and deployment of advanced vision-based perception systems for autonomous inspection robots, leveraging computer vision and AI expertise, and utilizing deep learning and machine vision techniques.

Key Highlights
Develop and deploy vision-based perception algorithms using deep learning and machine vision techniques
Design and implement supervised, self-supervised, and unsupervised learning methods for multi-modal data
Integrate perception pipelines into robotic systems using ROS1/ROS2
Key Responsibilities
Develop and deploy vision-based perception algorithms using deep learning and machine vision techniques
Design and implement supervised, self-supervised, and unsupervised learning methods for multi-modal data
Build and optimise models for 2D & 3D object detection and tracking, anomaly detection, LiDAR-based semantic segmentation and 3D point cloud understanding
Optimise models for edge deployment and deploy on NVIDIA Jetson platforms
Integrate perception pipelines into robotic systems using ROS1/ROS2
Technical Skills Required
PyTorch OpenCV MMDetection Detectron2 TensorRT ONNX Docker NVIDIA DeepStream ROS1 ROS2 AWS SageMaker Bedrock GitLab CI/CD MLflow n8n CVAT Label Studio 3D Point Labeler
Benefits & Perks
Fully remote

Job Description


Senior Computer Vision and AI Engineer


About the job

Edison Smart are searching for a Senior Computer Vision & AI Engineer to lead the development and deployment of advanced vision-based perception systems for autonomous inspection robots. This is a hands-on role focused on building, optimising, and deploying deep learning models across multi-modal sensor stacks in real-world robotic environments.


This is a fully remote contract opportunity, offering €80–100 per hour, for an initial 6-month engagement.


Key Responsibilities

Develop and deploy vision-based perception algorithms using deep learning and machine vision techniques (CNNs, ViTs, DETR-based models)

Design and implement supervised, self-supervised, and unsupervised learning methods for multi-modal data (RGB, LiDAR, thermal, etc.)

Build and optimise models for:

2D & 3D object detection and tracking

Anomaly detection

LiDAR-based semantic segmentation and 3D point cloud understanding

Optimise models for edge deployment (quantisation, pruning, distillation) and deploy on NVIDIA Jetson platforms (Xavier, Orin, Thor)

Integrate perception pipelines into robotic systems using ROS1/ROS2

Support and maintain MLOps workflows, ensuring reproducible training, evaluation, and CI/CD processes

Contribute to AWS-based AI pipelines (SageMaker, Bedrock, Lambda, S3) for scalable training and model lifecycle management

Drive research and innovation in multi-modal and 3D representations (Gaussian Splatting, NeRF, OpenCLIP embeddings)

Collaborate cross-functionally with robotics, software, and AI teams to improve autonomy, semantic mapping, and mission planning capabilities



Required Experience

Degree in Computer Science, Robotics, or a related technical field

2+ years’ professional experience in computer vision, deep learning, or robotic perception

Strong understanding of Vision Transformers (ViTs), CNNs, and DETR-based object detection architectures

Hands-on experience with PyTorch, OpenCV, MMDetection and/or Detectron2

Practical experience in model optimisation and deployment using TensorRT, ONNX, Docker, and/or NVIDIA DeepStream

Experience with data annotation tools such as CVAT, Label Studio, or 3D Point Labeler

Exposure to versioning and MLOps tools including GitLab CI/CD, MLflow, n8n, AWS SageMaker, and/or Bedrock

Strong programming skills in Python, C++, and Bash

Proven ability to work independently in fast-paced environments while collaborating effectively across teams

Fluent in English (German Desired)


Engagement Details

Contract position

€80–100 per hour

Fully remote

Initial 6-month engagement with potential extension

High-impact role on cutting-edge autonomous robotics programme


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