AI Engineer (Multimodal Systems)
PARIS, 75
il y a 5 jours
- Designs and implements AI components for in-game event recognition, multimodal learning, and model optimization
- Develops CV and audio processing pipelines for automated dataset generation and labeling
- Collaborates on training workflows for the top 100, 500, and 3000 games
- Builds the video decluttering pipeline to filter irrelevant gameplay segments
- Works closely with the Lead Engineer on model deployment optimization and SDK integration
- Implements and maintains C++ modules for data acquisition, inference, and model serving
- Focused on performance tuning and inference latency reduction for on-device intelligence
- Develop and optimize AI components for multimodal in-game event recognition, video dataset generation, and model deployment
- Build AI modules for CV/audio-based in-game event detection
- Implement data preprocessing and feature extraction pipelines
- Train, validate, and deploy models across top 100–3000 games
- Design video decluttering pipeline for gameplay quality refinement
- Collaborate with SDK developers for on-device inference optimization
- Ensure low-latency, high-accuracy inference performance
- Systematic approach to scalability, reproducibility, and deployment
- Multimodal data processing (video, audio, metadata)
- Rigorous analytical and debugging skills in performance-critical contexts
- Applied AI engineering and model lifecycle understanding
- Experience with OpenCV, PyTorch, or TensorFlow for model integration
- Experience with real-time inference and model compression for deployment
- Proficient in C++ for high-performance implementation
- Background in computer vision or audio event classification
- Familiarity with dataset management, labeling, and augmentation techniques
- Solid understanding of ML fundamentals (CNNs, transformers, multimodal fusion)
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