SRE for Scalable AI/ML Systems

TikTok USDS Joint Venture; San Jose (CA); On-site; USD 123,000 - 259,000; Full time

Job summary

TikTok USDS Joint Venture is seeking a Site Reliability Engineer for the Applied Machine Learning team. The role focuses on designing and running highly available ML systems, with the opportunity to optimize performance and automate operations.

You will work with a team providing 24/7 support and participate in on-call rotations, with a schedule that may include holidays. This position emphasizes reliability, security, and scalable system design.

Qualifications

• Expertise in analyzing and troubleshooting Linux-based distributed systems.
• Bachelor's or Master's degree in CS/CE or equivalent years of experience in a SRE or software engineering role.
• Experience programming with at least one commonly used language (C, C++, Python, Go).
• Strong understanding of data structures and algorithms.
• Competent knowledge of relational database systems.

Responsibilities

• Design, build, and maintain highly available, scalable, and fault-tolerant systems.
• Monitor and analyze system performance, identifying and resolving issues before causing user impact.
• Develop and maintain automated monitoring, alerting, and incident response systems.
• Collaborate closely with software engineering teams to ensure reliability, scalability, and performance in applications.
• Implement and maintain security best practices and ensure regulatory compliance.
• Provide 24/7 on-call support and scheduled shifts, which may include holidays.
• Conduct root cause analysis of incidents and implement preventative measures.
• Schedule is Monday to Friday, 12:00 AM to 10:00 AM PT.

Skills

Linux

Distributed systems

Python

Go

C/C++

Data structures & algorithms

Relational databases

System design

Automation

Performance analysis

Education

Bachelor's or Master's in CS/CE or equivalent experience

Tools

TensorFlow

PyTorch

MXNet

PaddlePaddle

Job description

TikTok USDS Joint Venture is seeking a Site Reliability Engineer for the Applied Machine Learning team. The role focuses on designing and running highly available ML systems, with the opportunity to optimize performance and automate operations.

You will work with a team providing 24/7 support and participate in on-call rotations, with a schedule that may include holidays. This position emphasizes reliability, security, and scalable system design.