Join us.

The Lead Ads team empowers TikTok's global monetization (billion-dollar business) via efficiently delivering lead ads on TikTok. Our mission is to push the boundaries of large-scale ads delivery systems and lead the innovations of TikTok's personalized online advertising. Hence, you'll have a chance to get deeply involved in our large-scale distributed systems and state-of-the-art machine learning algorithms. As a Machine Learning Engineer on the Lead Ads team, you will make efforts to develop novel machine learning solutions for ranking, build scalable foundations and launch various products that maximize the efficiency of lead ads delivery.

Key Responsibilities:
- Work on the development of a large-scale online ads delivery system and improve its accuracy.
- Explore multi-stage ranking models, conduct data analysis, develop feature engineering.
- Participate in the innovations of online ads systems using machine learning models, ranking algorithms, etc.
- Partner with product managers, data scientists and product strategy & operation team to launch new Lead Ads products and features.

Qualifications

Minimum Qualifications:
- BS/MS degree in Computer Science, Computer Engineering, or other relevant majors.
- 3+ years of hands-on experience with applying machine learning methods for ranking.
- 3+ years of software development experience and strong coding skills, especially in Python/C++. Experience with Tensorflow/PyTorch/MXNet is a plus.
- Experience with recommender system projects.
- Familiarity with online experimentation methods and analytics. Essential knowledge and skills in statistics.
- Curiosity toward new technologies and entrepreneurship.

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at tt.accommodations@tiktok.com

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $194000 - $355000 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

3. Exercising sound judgment.