Machine Learning Ops Engineer, Global SRE
TikTok
Sourced from TikTok's careers site · verified 5 hours ago
Description
MLOps - Global SRE team is responsible for the stability of machine learning systems under the Global Monetization Products and Technology organization, to ensure the stable and efficient operations of machine learning models from data preparation, development, training, deployment, serving and so on.
Responsibilities
1) Responsible for setting SLOs of online machine learning serving systems, maintaining the stability of the online serving systems.
2) Responsible for maintaining stability of offline machine learning training tasks, improving the success rate of the training tasks.
3) Responsible for rolling out GPU model training in Non-China regions.
4) Responsible for stability of AIGC related machine learning tasks.
5) Responsible for resource management and planning of machine learning resources, including: cost and budget, resource efficiency enhancement, offline and online resources tides, etc.
Requirements
Minimum Qualifications
1) Bachelor's degree in Computer Science or Software Engineering, similar technical field of study, or equivalent practical experience.
2) Expertise in Linux operating systems, networking, storage.
3) Experience programming in at least one of the following programming languages: Python, Go, C, C++, or Java.
4) Experience in troubleshooting application issues, or production operations.
5) Effective communication skills and a sense of ownership and drive.
Preferred qualifications:
1) Experience in SRE of machine learning systems.
2) Experience in SRE of ads/recommendation/search systems.
Skills
- linux
- networking
- storage
- python
- go
- c
- c++
- java
- machine learning
- sre
- ml systems
Summary
Maintain and troubleshoot machine learning systems' stability and efficiency.
Job title
Machine Learning Ops Engineer, Global SRE
Industry
software
Location
San Jose, CA
Salary
Pay not disclosed by employer
Visa sponsorship
Company has sponsored H-1B before
Management role
No
- Mar 29, 2026 First posted
- Mar 31, 2026 Removed from careers site Live 2 days
- Apr 1, 2026 Reposted
- Apr 1, 2026 Live now
As observed on the employer's careers site by ApplyAll. We show every change we've seen including removals.
Posting history Reposted 1×
- Mar 29, 2026 First posted
- Mar 31, 2026 Removed from careers site Live 2 days
- Apr 1, 2026 Reposted
- Apr 1, 2026 Live now
As observed on the employer's careers site by ApplyAll. We show every change we've seen including removals.
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