Machine Learning Engineer, Ads Creative

Description

A "creative" is the ad (in the form of a short-form video) served to TikTok users, composed of video, background music, call-to-action card, post-click landing page, and other formats that get delivered to users. A quote goes "creativity is the soul of advertising", because a good ad creative is effective, yet difficult to produce, especially at the scale of TikTok advertising.

The TikTok Ads Creative & Ecosystem team's mission is to solve the above dilemma, by building industry-leading tech solutions for ads creative/landing page understanding, production/generation, and optimization, to inspire and empower advertisers, creators, and other 3rd parties in the ecosystem to create and deliver the best engaging creative experiences to the end users. Our work is at the core of TikTok and creator monetization. Examples of our team's work include TikTok video editor, AI-powered smart video generation (we are also exploring AIGC), and TikTok creative exchange (a creative marketplace to connect TikTok advertisers with creators or third-party creative agencies).

We are user/product oriented and dedicated to technical excellence. We aim to drive and lead the technology renovation in the ads tech and creative industry, powering products and driving values for our clients, creators, and the whole ecosystem. We are excited to grow advertisers' and users' business understanding, build highly scalable and reliable software/infrastructure, partner across functions with global teams, and make big impacts. If you are someone who welcomes challenges, we are eager to have you on the team!

What You'll Do:
- Participate in the development of a large-scale Ads system.
- Responsible for the development of state-of-the-art applied machine learning projects.
- Own key targeting components or strategies in the TikTok ads monetization ecosystem.
- Work with product and business teams on product vision.

Requirements

Minimum Qualifications:
- BS/MS degree in Computer Science, Computer Engineering, or other relevant majors.
- Experience in and good theoretical grounding in machine learning concepts and techniques.
- Excellent programming, debugging, and optimization skills in one or more general purpose programming languages, including but not limited to: Go, C/C++, Python.
- Experience in one or more of the following frameworks: Tensorflow/PyTorch/MXNet, etc
- Ability to think critically and to formulate solutions to problems in a clear and concise way.

Preferred Qualification:
- Has experience in ads system, recommendation, searching, ranking, etc.