Senior Machine Learning Engineer – AIGC, Ads Creativity & Ecosystem 2233

San Jose, US-United States
Posted 7 months ago
About The Company

This company pioneers short-form video creation and social engagement, boasting a vast, engaged user base. Its platform empowers users with creative tools, filters, and effects. With a diverse content ecosystem, it’s a hub of creativity and expression. The proprietary algorithm ensures personalized content feeds, enhancing user engagement and satisfaction. This company wields significant influence on digital media, making it an invaluable partner for innovative collaborations and marketing endeavors.


What You’ll Do

– Engage in and improve the whole lifecycle of Ads systems — from system design consulting through to launch reviews, deployment, operation and refinement.
– Build availability of services deployed across multiple data centers globally.
– Deliver tools/software to improve the reliability, scalability and operability of services.
– Measure and monitor availability, latency and overall service health.
– Practice sustainable incident response and postmortems.
– Participate in on-call rotations across continents.


REQUIREMENT
Position Requirements
Minimum Qualifications
– Bachelor’s degree in Computer Science, similar technical field of study, or equivalent practical experience.
– 5+ years of experience in programming in at least one of the following programming languages: C, C++, Java, Python, Perl, or Go.
– Expertise in Unix/Linux operating systems, IP networking.
– Experience in problem solving, application issues, or production operations.
– Experience in automating routine tasks.
– Effective communication skills and a sense of ownership and drive.


Preferred Qualifications
– Experience in SRE of Ads/recommendation systems.
– Experience designing, analyzing and troubleshooting large-scale distributed systems.

Job Features

Job CategoryAI Engineering
SeniorityStaff IC / Senior Staff IC / Architect
Base Salary$160,000 - $320,000
Recruiterjenny.yang@ocbridge.ai

Apply Online