Machine Learning Engineer, TikTok BRIC Account Takeover

Responsibilities

The Business Risk Integrated Control (BRIC) team is missioned to:
- Protect TikTok users, including and beyond content consumers, creators, advertisers;
- Secure platform health and community experience authenticity;
- Build infrastructures, platforms and technologies, as well as to collaborate with many cross-functional teams and stakeholders.

The BRIC team works to minimize the damage of inauthentic behaviors on TikTok platforms (e.g. TikTok, CapCut, Lark), covering multiple classical and novel community and business risk areas such as account integrity, engagement authenticity, anti spam, API abuse, growth fraud, live streaming security and financial safety (ads or e-commerce), etc.
In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives, especially in building scalable and robust, intelligent and privacy-safe, secure and product-friendly systems and solutions. Our challenges are not some regular day-to-day technical puzzles -- You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolvement of a phenomenal product eco-system. The work needs to be fast, transferrable, while still down to the ground to making quick and solid differences.

Responsibilities:
- Take ownership of account security issues across TikTok and other overseas product lines (short video, live streaming, payment, e-commerce, local services, etc.).
- Leverage large-scale behavioral data from hundreds of millions of accounts, applying algorithms to mine massive datasets and identify various account security issues, including but not limited to fake registrations, account takeovers, account trading, account nurturing, and session hijacking.
- Analyze and uncover hidden data correlations to build an account risk perception framework, enabling early detection and rapid response to emerging risks.
- Contribute to the development of account risk control infrastructure, including data warehouses, feature engineering, and machine learning models.

Qualifications

Minimum Qualifications:
- Master's degree or above in Computer Science, Statistics, Artificial Intelligence, or a related field.
- Solid engineering skills. Proficiency in one or more programming languages such as C++, Java, or Python.
- Familiarity with big data technologies such as SQL/HQL, and hands-on experience with one of Hadoop, Hive, Spark, or Flink.
- Solid understanding of machine learning, deep learning, and large language models; knowledge of clustering, community detection, and related techniques, with the ability to validate algorithm effectiveness and apply them to risk control scenarios.

Preferred Qualifications:
- Prior experience in combating online fraud, abuse, or anti-cheating in the internet industry .
- Familiarity with emerging technologies such as large language models (LLMs) and AI Agents.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $136800 - $259200 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.