ML Infra Engineer for Global High-Performance Recs

TIKTOK PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Career growth

Paid leave

Flat structure

Job summary

TikTok PTE. LTD. is hiring for a role in our Recommendation Architecture Team in Singapore.

You will contribute to building and optimizing the architecture for our recommendation system to deliver stable, high-performance experiences for users globally. The role entails research, design and development of software for large-scale ML systems, and close collaboration with hardware engineers to meet performance requirements.

Qualifications

• Bachelor's degree in Computer Science or related field with experience building scalable systems.
• Experience with at least one or two programming languages in Linux such as C/C++/Go.
• Understand GPU hardware architecture, GPU software stack (CUDA, cuDNN), and have experience in GPU performance analysis.

Responsibilities

• Serve and train infra optimization of machine learning models.
• Build and maintain high performance online services for TikTok recommendation system.
• Build globalized large-scale recommendation system.
• Research, design, and develop computer and network software or specialized utility programs.
• Analyze user needs and develop software solutions, applying principles of computer science and engineering.
• Update software, enhance existing capabilities, and develop testing and validation procedures.
• Collaborate with hardware engineers to integrate hardware and software systems and define performance requirements.

Skills

C/C++/Go

Linux

GPU architecture

Education

Bachelor's in Computer Science or related

Tools

CUDA

cuDNN

Job description

TikTok PTE. LTD. is hiring for a role in our Recommendation Architecture Team in Singapore.

You will contribute to building and optimizing the architecture for our recommendation system to deliver stable, high-performance experiences for users globally. The role entails research, design and development of software for large-scale ML systems, and close collaboration with hardware engineers to meet performance requirements.