MLOps Engineer Intern: Build Scalable AI Systems

TikTok; Singapore; Presencial; SGD 17.000 - 22.000; A tiempo parcial

Descripción de la vacante

TikTok is offering an internship with a focus on SRE for machine learning infrastructure. You will work on the reliability of online inference services and offline training pipelines, while helping optimize resources and deploy new ML frameworks.

Ideal candidates are pursuing CS/SE degrees, comfortable with Linux, and experienced in Python/Go/C/C++/Java. This internship provides hands-on learning, industry exposure, and opportunities for professional growth in a fast-paced tech environment.

Formación

• Pursuing Undergraduate/ Master’s in Computer Science or Software Engineering.
• Experience with Linux, networking, and storage.
• Proficient in Python, Go, C, C++, or Java.
• Experience troubleshooting production systems.
• Strong communication and ownership skills.

Responsabilidades

• Define and drive SLOs for online ML inference systems ensuring reliability and performance.
• Ensure reliability of offline ML training pipelines and improve training job success rates.
• Drive infrastructure capacity planning for ML workloads and optimize GPU/CPU utilization.
• Lead enablement of new ML frameworks and GPU platforms for large-scale deployment.
• Design, build, and maintain MLOps platforms and automation tools.

Conocimientos

Linux

Networking

Python

Go

C++

Java

Troubleshooting

Communication

Educación

Undergraduate/ Master’s in Computer Science or Software Engineering

Herramientas

Git

Docker

Descripción del empleo

TikTok is offering an internship with a focus on SRE for machine learning infrastructure. You will work on the reliability of online inference services and offline training pipelines, while helping optimize resources and deploy new ML frameworks.

Ideal candidates are pursuing CS/SE degrees, comfortable with Linux, and experienced in Python/Go/C/C++/Java. This internship provides hands-on learning, industry exposure, and opportunities for professional growth in a fast-paced tech environment.