Machine Learning Engineer (Ads Core) - User Experience

Responsibilities

Ads Core team is chartered to build key monetization components across various ad delivery stages:
1. We build up ranking, bidding, budget, format, diagnosis and other frameworks that serve as a mid platform to enable other ad teams to iterate their products in parallel.
2. We implement outstanding traffic strategies to maximize revenue under the constraint of user experience and achieve complete exploration of advertiser's audience.
3. Our model driven automation solutions optimize ad delivery performance from end to end.

Responsibilities:
1. Participate in and take charge of algorithm optimization for user ad experience in TikTok's global business, optimize the conversion efficiency between ad revenue and user experience by intervening in the ad bidding and ranking logic via signals, and realize the sustainable and sound development of the ad ecosystem;
2. Responsible for the end-to-end technical iteration of advertising experience optimization, covering three core modules: sorting upgrade, duplication governance, and crowd strategy scheduling, and continuously improve the collaborative efficiency of experience and monetization through underlying model infrastructure and strategy innovation;
3. Deeply explore user behavior feedback and experience pain points, and systematically solve core user experience issues through end-to-end technology upgrade, covering areas including engagement model optimization, implementation of personalized frequency distribution, and upgrade of user sensitivity modeling;
4. Lead the underlying capability building based on LLM, implement user intent recognition and semantic understanding technology for advertising content, integrate multimodal representation capabilities with the large model as the core, and provide core capability support for end-to-end experience optimization strategies.

Qualifications

Minimum Qualifications:
- Possess excellent coding skills, solid foundation in data structures and algorithms, as well as solid theoretical knowledge and practical experience in machine learning and deep learning;
- Be familiar with at least one mainstream deep learning programming framework (TensorFlow/PyTorch), and have a good command of its underlying architecture and implementation mechanism;
- Excellent ability to analyze and solve problems, with a strong passion for tackling challenging issues;
- Have a passion for technology, as well as excellent communication skills and team spirit.

Preferred Qualifications:
- Have work experience related to models or customer ecosystem in advertising and recommendation scenarios;
- Have published papers at relevant conferences such as ICML, NIPS, ICLR, RecSys, KDD, etc. ;
- Experience in open-source communities of deep learning programming frameworks.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $218400 - $480000 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.

For Los Angeles County (unincorporated) Candidates:

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:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and