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# AI Engineer (Multimodal Systems)

- **Company:** Razer
- **Location:** Paris, France
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Audio Signal Processing, C++ (Programming Language), Software Debugging, OpenCV, Performance Tuning, Tensorflow, Model Compression, Systems Integration, Data Processing, Multimodal Learning, Pytorch, On-device Inference, Real-time Inference, Machine Learning Operations, Feature Extraction, Multimodal Fusion
- **Published:** October 29, 2026
- **Apply:** https://www.welcometothejungle.com/en/companies/razer/jobs/ai-engineer-multimodal-systems_paris_nqhn5lwe

## About the Role

* 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)

## Description

* 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