Responsibilities

The TikTok-BRIC-ML Foundation team builds scalable ML and AI platforms that form the backbone of TikTok's risk control intelligence. It powers everything from model training and deployment to A/B testing and real-time inference. Our scope extends to cutting-edge AI infrastructure and LLM applications -- including AI agents, LLM inference services, and monitoring systems-that enable safer, smarter, and more trustworthy user experiences across the platform. In this team you'll have a unique opportunity to have first-hand exposure to the strategy of the company in key security initiatives. You'll be part of a team that's developing novel solutions to first-seen challenges of a non-stop evolution of a phenomenal product eco-system: - Work on infrastructure and tools to enable construction, deployment, and serving of risk defence algorithms and machine learning models at scale. Improve capacities of risk prevention, perception and remediation across various TikTok businesses. - Build tools and automated procedures to support risk analytics and defence enforcement. - Keep risk control solutions state-of-art in front of data security, modularisation, privacy and compliance. Help improve end-to-end risk service/platform/tooling SLA. - Lead technical direction for cross-team initiatives and mentor engineers in best practices for risk infrastructure and tooling. Responsibilities - Build and maintain modeling infrastructures, LLM applications to mitigate business risks in TikTok products/platforms, reduce modeling, operational, and system load on risk adversaries and new product/risk ramping-ups. - Uplevel risk machine learning excellence in privacy/compliance, interpretability, risk perception and analysis.

Qualifications

Minimum Qualifications: - Experience with one or more general purpose programming languages including but not limited to: Go, C/C++, Java, Python - Ability to think critically and formulate solutions to problems in a clear and concise way - Solid communication and collaboration skills with the ability to work effectively with internal teams in a cross-cultural and cross-functional environment Preferred Qualifications: - Bachelor or above degree in Computer Science, Computer Engineering or relevant majors. - Experience in machine learning infrastructure that handles large traffic - Experience in Risk related system (or known as Anti-abuse system, or Trust related domain), or large distributed systems.

Job Information

[For Pay Transparency]Compensation Description (Annually)

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.

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.