AI Engineer (Multimodal Systems) Razer
Gaming hardware and payment services for optimal gamer experience.
CDI
Paris
Télétravail total
Salaire : non spécifié
> 1 an
Les compétences que l’on cherche
IA et machine-learning
C++
TensorFlow
Pytorch
OpenCV
Votre nouvelle entreprise
1600 collaborateurs
Logiciels
L'avis de Welcome
Razer is a truly unique, all-encompassing lifestyle brand for gamers; it not only manufactures innovative gaming tech but also doubles as an in-game payments service, named Razer Gold. In 2018, the company also created a digital payment network for businesses and consumers across Southeast Asia. Since entering the fintech market in SE Asia, Razer Fintech has become one of the largest online-to-offline digital payment networks in the market, tapping into Southeast Asia’s 430 million-plus unbanked and underserved population. Razer Gold has also seen substantial success, as it is one of the world's largest virtual credit services for gamers. With this sort of creativity and a strong understanding of its market, Razer has been able to disrupt gamer-focused ecosystems around the globe. Its expansive catalogue of gaming hardware ranges from laptops to headsets to chairs, whereas its suite of software platform options brings in over 70 million users. The company is recognised as the leading brand for gamers in the USA, Europe, and China and is comfortably secure in maintaining that position.
Vos missions au quotidien
- 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
Ce que l’on cherche
- 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)