Machine Learning Engineer, Ads Creative

A "creative" is the ad (in the form of a short-form video) served to Tik Tok 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 Tik Tok advertising.

The Tik Tok 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 Tik Tok and creator monetization.

Examples of our team's work include Tik Tok video editor, AI-powered smart video generation (we are also exploring AIGC), and Tik Tok creative exchange (a creative marketplace to connect Tik Tok 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!

• 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 Tik Tok ads monetization ecosystem.
• Work with product and business teams on product vision.

• 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.

• Has experience in ads system, recommendation, searching, ranking, etc.

The base salary range for this position in the selected city is $156000 - $316800 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems;
• Exercising sound judgment.