Senior Software Engineer / Lead (AI/ML Platform)
Razer Inc.Singapore, Singapore
Posted January 16, 2026
Full Time
About the Company
Razer™ is the world’s leading lifestyle brand for gamers. The triple-headed snake trademark of Razer is one of the most recognized logos in the global gaming and esports communities. With a fan base that spans every continent, the company has designed and built the world’s largest gamer-focused ecosystem of hardware, software and services. Razer’s award-winning hardware includes high-performance gaming peripherals and Blade gaming laptops. Razer’s software platform, with over 70 million users, includes Razer Synapse (an Internet of Things platform), Razer Chroma™ (a proprietary RGB lighting technology system), and Razer Cortex (a game optimizer and launcher). In services, Razer Gold is one of the world’s largest virtual credit services for gamers, and Razer Fintech is one of the largest online-to-offline digital payment networks in SE Asia. Founded in 2005 and dual-headquartered in Irvine and Singapore, Razer has 18 offices worldwide and is recognized as the leading brand for gamers in the USA, Europe and China.
Job Description
Join Razer on a global mission to revolutionize the way the world games. As a Senior Software Engineer / Lead (AI/ML Platform), you will design and build an AI/ML platform capable of high-throughput training and inference across local and cloud GPU environments.
Requirements
- 8+ years of experience in software engineering, ML infrastructure, or high-performance computing
- Hands-on experience designing and operating both local GPU servers and cloud GPU environments
- Deep knowledge of transformer-based model inference and training optimization
- Experience building high-availability distributed systems
- Strong proficiency in Python and at least one systems language (C++ or Go)
- Experience with deep learning frameworks (PyTorch, TensorFlow) and inference engines (vLLM, SGLang, TensorRT, Triton)
- Solid understanding of distributed systems, parallel computing, and container orchestration (Docker, Kubernetes)
- Solid understanding of GPU programming (CUDA or ROCm), GPU memory hierarchy, and performance tuning
- Strong collaboration and communication skills; ability to lead engineering efforts
Benefits
- Competitive salary
- Opportunities for growth and professional development
- Collaborative and inclusive work environment