AI Engineer (Multimodal Systems)

Join our team as an AI Engineer specializing in multimodal systems.

About Razer

Solid understanding of ML fundamentals (CNNs, transformers, multimodal fusion)

Responsibilities

• In this role, you will design and implement AI components for in-game event recognition, multimodal learning, and model optimization.
• You will develop computer vision and audio processing pipelines, collaborate on training workflows for various games, and build a video decluttering pipeline.
• You will work closely with the Lead Engineer on model deployment optimization and SDK integration, and implement and maintain C++ modules for data acquisition, inference, and model serving.
• Your focus will be on performance tuning and inference latency reduction for on-device intelligence.
• Design and implement AI components for in-game event recognition, multimodal learning, and model optimization.
• Develop computer vision and audio processing pipelines for automated dataset generation and labeling.
• Collaborate on training workflows for the top 100, 500, and 3000 games, and build the video decluttering pipeline to filter irrelevant gameplay segments.
• Systematic approach to scalability, reproducibility, and deployment
• Multimodal data processing (video, audio, metadata)
• Rigorous analytical and debugging skills in performance-critical contexts

Requirements

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

Preferred

• Familiarity with dataset management, labeling, and augmentation techniques