Machine Learning Ops Engineer Graduate (Ads Infra) - 2027 Start

TikTok Pte. Ltd.; Singapore; On-site; SGD 60,000 - 90,000; Full time

Job summary

TikTok Pte. Ltd. in Singapore is seeking a graduate SRE to join our global ML infrastructure team. You will help define SLOs, ensure reliability of online ML inference services, and support training pipelines and deployment workflows across large-scale systems.

You will work with Linux, Python/Go/C/C++/Java, and modern observability tools to improve GPU/CPU utilization, monitoring, and performance. Join a fast-paced team driving scalable ML platforms.

Qualifications

• Bachelor's or Master's degree in Computer Science or Software Engineering or related discipline.
• Strong knowledge of Linux operating systems, networking and storage.
• Proficiency in at least one language: Python, Go, C, C++, or Java.
• Experience in troubleshooting applications or production operations.
• Excellent communication and ownership skills.

Responsibilities

• Define and drive SLOs for online ML inference systems to ensure reliability and performance of large-scale production services.
• Ensure reliability and operational excellence of offline ML training pipelines and improve training job success rates.
• Lead capacity planning and resource management for ML workloads, optimizing GPU/CPU utilization.
• Enable new ML frameworks and GPU platforms for scalable production deployments while preserving model quality.
• Design and maintain MLOps platforms and automation tools (quota management, diagnostics, monitoring, observability, resource management).

Skills

Python

Go

C

C++

Java

Linux

Networking

Storage

Troubleshooting

Communication

Ownership

Education

Bachelor's degree in Computer Science or Software Engineering

Master's degree in Computer Science or related field

Job description

Responsibilities

Team Introduction MLOps

• Global SRE team is responsible for the reliability of the machine learning infrastructure powering ByteDance’s global advertising systems.

We ensure the stability, scalability, and operational efficiency of the entire machine learning lifecycle, including data pipelines, model development, training, deployment, inference, monitoring, and continuous optimization. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.

The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis

Responsibilities

• Define and drive Service Level Objectives (SLOs) for online machine learning inference systems, ensuring the reliability, availability, and performance of large-scale production inference services;
• Ensure the reliability and operational excellence of offline machine learning training pipelines, continuously improving training job success rates;
• Drive infrastructure capacity planning and resource management for machine learning workloads, ensuring compute resources meet evolving business demands while continuously improving GPU and CPU utilization through performance optimization;
• Lead the enablement of new machine learning frameworks and GPU platforms, driving large-scale production deployment while maintaining model quality and business performance;
• Design, build, and maintain MLOps platforms and automation tools, including quota management, job diagnostics, monitoring and observability, resource management, and operational tooling.

Qualifications

Minimum Qualifications

• Individuals who are completing or have recently completed a Bachelor's/ Master's degree in Computer Science or Software Engineering or a related discipline.
• Expertise in Linux operating systems, networking, storage.
• Experience programming in at least one of the following programming languages: Python, Go, C, C++, or Java.
• Experience in troubleshooting application issues, or production operations.
• Effective communication skills and a sense of ownership and drive.

Preferred Qualifications

• Experience in SRE of machine learning systems.
• Experience in SRE of ads/recommendation/search systems.