AI Engineer, Multimodal Systems

Joining Razer places you on a global mission to revolutionize the gaming experience.

Job Responsibilities

• 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.
• Build a video decluttering pipeline to filter irrelevant gameplay segments and refine gameplay quality.
• Work closely with the Lead Engineer on model deployment optimization and SDK integration.
• Implement and maintain C++ modules for data acquisition, inference, and model serving, focusing on performance tuning and inference latency reduction for on‑device intelligence.
• Train, validate, and deploy models, ensuring low‑latency, high‑accuracy inference across games.

Competencies

• Applied AI engineering and model lifecycle understanding.
• Multimodal data processing (video, audio, metadata).
• Rigorous analytical and debugging skills in performance‑critical contexts.
• Systematic approach to scalability, reproducibility, and deployment.

Pre‑Requisites

• Proficient in C++ for high‑performance implementation.
• Solid understanding of ML fundamentals (CNNs, transformers, multimodal fusion).
• Experience with OpenCV, PyTorch, or TensorFlow for model integration.
• Background in computer vision or audio event classification.
• Familiarity with dataset management, labeling, and augmentation techniques.
• Experience with real‑time inference and model compression for deployment.

Equal Opportunity Employer

Razer is proud to be an Equal Opportunity Employer. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. We provide reasonable accommodations where needed to ensure every team member can perform and contribute at their best.