Energy Robotics
Robot Software Engineer(m/w/x)
Vollzeitmit HomeofficeBerufserfahren
Darmstadt
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ENEnergy Robotics
Computer Vision & AI Engineer(m/w/x)
Darmstadt
Vollzeitmit HomeofficeBerufserfahren
AI/ML
Nejo KI-Zusammenfassung
Developing vision-based perception algorithms for autonomous inspection robots at a mobile robotics software firm, with LiDAR 3D point cloud understanding. 2+ years in computer vision or robot perception with ViTs/CNNs/DETR models and PyTorch/TensorRT experience required. Annual education budget, flexible remote work, and 1:1 psychologist sessions.
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Anforderungen
- Degree in Computer Science, Robotics, or related technical field
- 2+ years of professional experience in computer vision, deep learning, or robot perception
- Strong understanding of Vision Transformers (ViTs), Convolutional Neural Networks (CNNs), and DETR-based models for object detection
- Hands-on experience with frameworks including PyTorch, OpenCV, MMDetection, and/or Detectron2
- Applied experience in Optimization & Deployment with TensorRT, ONNX, Docker, and/or NVIDIA DeepStream
- Direct experience with Data Annotation using CVAT, and/or Label Studio, and/or 3D Point Labeler
- Practical experience in Versioning & MLOps using GitLab CI/CD, MLflow, n8n, AWS SageMaker, and/or Bedrock
- Strong programming skills in Python, C++, Bash
- Strong analytical, problem-solving, and growth mindset
- Excellent collaboration between cross-functional AI and robotics teams
- Passion for innovation, autonomy, and pushing the boundaries of perception systems
- Ability to work independently and manage multiple priorities in a fast-paced environment
- Fluent in English
- Experience with LLMs, VLMs, VLAs and multi-modal embeddings
- Familiarity with semantic scene graphs-based 3D Gaussian splatting
- Exposure to cloud-based data services or AI workflow orchestration
- Contributions to open-source projects in AI/robotics or publications in the field
Aufgaben
- Develop and deploy vision-based perception algorithms for autonomous inspection robots
- Design and implement supervised, self-supervised, and unsupervised learning methods for multi-modal data
- Build and optimize models for object detection and tracking
- Implement anomaly detection techniques
- Conduct LiDAR-based semantic segmentation and 3D point cloud understanding
- Optimize models for on-device inference through quantization, pruning, and distillation
- Deploy models on edge hardware like NVIDIA Jetson Xavier/Orin/Thor
- Integrate perception pipelines into robotic systems using ROS1/ROS2
- Collaborate with software and robotics teams
- Support MLOps workflows for reproducible training and evaluation of AI models
- Maintain cloud-based AI pipelines on AWS for scalable training and inference
- Contribute to research on multi-modal and 3D representations
- Participate in the continuous improvement of AI infrastructure for mission planning and robot autonomy
Berufserfahrung
- 2 - 5 Jahre
Ausbildung
- Bachelor-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- PyTorch
- OpenCV
- MMDetection
- Detectron2
- TensorRT
- ONNX
- Docker
- NVIDIA DeepStream
- CVAT
- Label Studio
- 3D Point Labeler
- GitLab CI/CD
- MLflow
- n8n
- AWS SageMaker
- Bedrock
- Python
- C++
- Bash
Benefits
Sonstige Zulagen
- Annual education budget
- Kindergarten cost allowance
Weiterbildungsangebote
- Knowledge-sharing sessions
Flexibles Arbeiten
- Flexible remote work
Ergonomischer Arbeitsplatz
- Support for standing desk
Mentale Gesundheitsförderung
- 1:1 sessions with psychologists
- Mental health workshops
Team Events & Ausflüge
- Team events
- Weekly sponsored team lunches
Öffi Tickets
- Support for public transport costs
Betriebliche Altersvorsorge
- Extra employer contribution to pension scheme
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens Energy Robotics erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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