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Computer Vision Engineer – Object Detection at Autonomous Teaming Solutions ATS GmbH · Katori

Asks for

The ad says“Hands-on experience in dataset collection, labeling, augmentation, and training”
The ad says“Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)”
The ad says“Strong experience with temporal models such as RNNs, ConvLSTMs, or transformer-based tracking”
The ad says“Hands-on experience in dataset collection, labeling, augmentation, and training”
The ad says“Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)”
The ad says“Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)”
The ad says“Proficiency in PyTorch, Python, Git, Docker”
The ad says“Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)”
The ad says“Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)”
The ad says“Proficiency in PyTorch, Python, Git, Docker”
The ad says“Hands-on experience in dataset collection, labeling, augmentation, and training”
The ad says“Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)”
The ad says“Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)”
The ad says“Proficiency in PyTorch, Python, Git, Docker”
The ad says“Proficiency in PyTorch, Python, Git, Docker”
The ad says“Strong experience with temporal models such as RNNs, ConvLSTMs, or transformer-based tracking”
The ad says“Strong experience with temporal models such as RNNs, ConvLSTMs, or transformer-based tracking”
The ad says“Hands-on experience in dataset collection, labeling, augmentation, and training”
The ad says“Strong experience with temporal models such as RNNs, ConvLSTMs, or transformer-based tracking”
The ad says“Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)”

What we offer

Work in an international, agile team creating the future of autonomous systems
Grow your career in a expanding and ambitious engineering team
Build innovative products using state-of-the-art technologies in AI, robotics, and autonomy
Benefit from a steep learning curve and continuous development
Enjoy team events and a strong, collaborative culture

Your mission

Build, adapt, and train neural networks for object detection and perception tasks using time-series data
Implement perception algorithms that extract and leverage temporal context across multiple frames
Design, implement, and optimize custom loss functions, augmentations, and architectures
Collect, prepare, and curate datasets from the real world – not pre-cleaned academic datasets
Supervise data annotation by refining labeling guidelines and assuring adherence to them
Evaluate and debug models using AP, Precision/Recall, mIoU, and video-based metrics
Deploy models into production as part of an integrated multi-sensor system (camera, radar, IR, acoustic, etc.)

Your profile

Strong experience in computer vision and deep learning, with a focus on object detection using one-stage or two-stage models (YOLO, FCOS, DETR, Faster R-CNN, etc.)
Strong experience with temporal models such as RNNs, ConvLSTMs, or transformer-based tracking
Ability to modify and extend network architectures, not just use them off the shelf
Hands-on experience in dataset collection, labeling, augmentation, and training
Proven ability to train object detection models from scratch or adapt them to custom classes and data
Familiarity with perception challenges specific to robotics, such as motion blur, lighting variation, occlusion, or limited compute
Proficiency in PyTorch, Python, Git, Docker

Nice to have

Experience with tracking algorithms (DeepSORT, ByteTrack, Kalman Filters).
Prior work with non-visual sensors such as infrared, acoustic, radar, or LiDAR for object detection and fusion.
Exposure to model optimization and compression (quantization, pruning, distillation).
Experience in the domain of UAVs, familiarity with ROS.

What else

Intrinsic motivation, attention to detail, and strong problem-solving mindset
Creative thinker with a structured and systematic approach
Humble and collaborative — prioritizes collective success over individual recognition
High ethical standards and disciplined work ethic
Extra-curricular leadership or achievements are a bonus
Fluent in English
Nationality of a NATO member nation or close ally is required
Successful candidates will be required to obtain security clearance

Why us?

Join us to shape the future of AI-driven defense!

Do you feel that you fit the description, but don't think you fulfill all the criteria 100%? Apply to us anyway. 
We look forward to receiving your detailed application via our online form. 

The world is changing. Exponential technologies are enabling new types of security threats. We are committed to staying ahead by building nimble, scalable, and cost-effective defences. We are looking for passionate developers who are eager to create exceptional products, safeguard our freedom, and strengthen the resilience of democracies.