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Research Scientist Graduate (Ads Creative)

TikTok · San Jose, CA · 8月2日 · 1个月前
CSO 可内推 硕士 机器学习/AI
评分
71
发布日期
8月2日 (1个月前)
签证支持
支持 (该雇主近年 H-1B 批准 442 例)
内推
有 CSO 内推渠道
公司规模
10k+
行业
互联网

岗位描述

We are Creative AI team under Monetization Technology. Our team focuses on developing cutting-edge Generative AI techs across all modalities, including text, image, videos, landing pages, etc., and creates industry-leading technical solutions to improve creative efficiency for advertisers, agencies and creators. We are committed to automated creative workflows by leveraging Generative AI technologies, to increase overall revenue for advertisers, agencies and creators.

We aim to drive and lead the generative AI in the ads tech and creative industry, powering products and driving values for our clients, creators, and the whole ecosystem.

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 - we encourage you to apply early.

Responsibilities

  • Optimize the post training of advertising video generation based on the latest generative models and technologies
  • Analyze the reasons behind high-quality advertisement videos and the defective parts in AIGC videos via multimodal video understanding.
  • Train the reward model based on the ad delivery data of video ads to guide the optimization of the video generation model.

Minimum Qualifications

  • Individuals who are completing or have recently completed a Master's degree in Computer Science, Machine Learning, or a related discipline.
  • Strong publications record in top conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, etc).

Preferred Qualifications

  • Hands-on experience of developing multimodality foundation models and work or internship experience in an AI research organization is a plus.

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