Autonomous Teaming

Computer Vision Engineer – Object Detection

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Stellenbeschreibung:


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.)
  • 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.
Meta 
  • 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 
  • 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.

About us


We are a defence-tech start-up specializing in machine vision solutions. If you have a passion for cutting-edge innovation, and drive to use your skills to create next generation solutions, this is an opportunity for you
What we do: We are developing solutions that enable computers and sensors to collaborate as teams, working together to address emerging security challenges. Our primary mission is to defend against AI-powered asymmetric threats at scale, such as drone swarms and other UXVs.
Who we are: Based in Munich, Berlin and Bordeaux/Toulouse we are rapidly expanding across Europe with plans to open more office hubs soon. We embrace a hybrid work culture - valuing the collaborations that happens in the office, while also empowering our team members to work remotely with responsibility and autonomy. 
NOTE / HINWEIS:
EnglishEN: Please refer to Fuchsjobs for the source of your application
DeutschDE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung

Stelleninformationen

  • Veröffentlichungsdatum:

    29 Nov 2025
  • Standort:

  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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