Machine Learning Engineering Manager - TikTok Community Health

Responsibilities

The TikTok-BRIC-Community Health is responsible for addressing ecosystem risks in TikTok content creation, distribution, and social interactions, with a focus on combating underground industries facilitated by fake accounts, large-scale coordinated groups, and content or behaviors that harm community health and experience. We are looking for an experienced Machine Learning Engineering Manager to lead the US site of the team, responsible for combating fake account registration and protecting the integrity of social engagement.

You will be at the forefront of protecting our community, tackling unique and evolving challenges in a dynamic global environment. This role offers a significant opportunity to influence company strategy and build innovative solutions to ensure a safe and positive user experience.

Responsibilities
- Lead the technical direction and strategy for the team, focusing on community health and user safety
- Develop, deploy, and maintain sophisticated machine learning models and strategies to detect and mitigate risks such as fake accounts and inauthentic engagement.
- Architect and build robust, scalable systems for real-time risk detection and enforcement.
- Manage the day-to-day operations of the machine learning engineering team, fostering a culture of technical excellence, innovation, and continuous improvement
- Partner closely with Product Managers, Data Scientists, and Operations teams to define the technical roadmap, set clear milestones, and ensure the timely delivery of key initiatives
- Mentor and grow a team of talented engineers, providing technical guidance and career development support
- Communicate complex technical concepts and project outcomes to both technical and non-technical stakeholders

Qualifications

Minimum Qualifications:
- Proven experience as a manager with a strong track record of leading, mentoring, and growing a Machine Learning Engineering (MLE) team.
- Solid foundation in machine learning theory and practice, with demonstrated experience in areas like deep learning, NLP, graph-based learning, or large-scale classification systems.
- Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional, fast-paced environment.

Preferred Qualifications:
- Experience in the Trust & Safety, content moderation, anti-spam, or risk control domain.
- Hands-on experience building detection systems for fake accounts, coordinated networks (e.g., using graph neural networks), or harmful content at scale.
- Solid software engineering skills with proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hive).

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $208800 - $438000 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;