Machine Learning Engineer Graduate (BRIC) - 2026 Start (PhD)
Responsibilities
The Business Risk Integrated Control (BRIC) team is searching for talented interns to help us solve one of the internet's toughest challenges: protecting a global community from sophisticated, adversarial threats.
We are the engineering team responsible for the security and authenticity of TikTok, CapCut, and more. We stop spam, shut down fraud, prevent account takeovers, and ensure the interactions on our platform are genuine.
What you'll do:
- Tackle Real-World Adversarial Problems: You'll work on detecting fake engagement, API abuse, and financial fraud.
- Build Models at Massive Scale: Your work will involve analyzing billions of data points to find and stop bad actors.
- Push the Boundaries of AI: You'll have the chance to work with state-of-the-art techniques like Graph Neural Networks (GNNs), Transformers, and LLMs to model complex user behavior.
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We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.
Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible.
Responsibilities:
• Build machine learning solutions to respond to and mitigate business risks in TikTok products/platforms. Such risks include and are not limited to abusive accounts, fake engagements, spammy redirection, scraping, fraud, etc.
• Improve modeling infrastructures, labels, features and algorithms towards robustness, automation and generalization, reduce modeling and operational load on risk adversaries and new product/risk ramping-ups.
• Uplevel risk machine learning excellence on privacy/compliance, interpretability, risk perception and analysis.
Qualifications
Minimum Qualifications
• PhD degree in Computer Science or related fields or equivalent practical experience
• Final year or recent graduate with a background in Computer Science, Statistics, or other relevant, machine-learning-heavy majors.
• Solid engineering skills. Familiar with at least two: Linux, Hadoop, Hive, Spark, Storm.
• Ability to think critically, objectively, rationally. Reason and communicate in result-oriented, data-driven manner. High autonomy.
Preferred Qualifications
• Strong machine learning background. Proficiency or publications in modern machine learning theories and applications such as deep neural nets, transfer/multi-task learning, reinforcement learning, time series or graph unsupervised learning.
• Curiosity towards new technologies and entrepreneurship
• High levels of creativity and quick problem-solving capabilities
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.
Perks and Benefits
Health and Wellness
- Health Insurance
- Dental Insurance
- Vision Insurance
- HSA
- Life Insurance
- Fitness Subsidies
- Short-Term Disability
- Long-Term Disability
- On-Site Gym
- Mental Health Benefits
- Virtual Fitness Classes
Parental Benefits
- Fertility Benefits
- Adoption Assistance Program
- Family Support Resources
Work Flexibility
- Flexible Work Hours
- Hybrid Work Opportunities
Office Life and Perks
- Casual Dress
- Snacks
- Pet-friendly Office
- Happy Hours
- Some Meals Provided
- Company Outings
- On-Site Cafeteria
- Holiday Events
Vacation and Time Off
- Paid Vacation
- Paid Holidays
- Personal/Sick Days
- Leave of Absence
Financial and Retirement
- 401(K) With Company Matching
- Performance Bonus
- Company Equity
Professional Development
- Promote From Within
- Access to Online Courses
- Leadership Training Program
- Associate or Rotational Training Program
- Mentor Program
Diversity and Inclusion
- Diversity, Equity, and Inclusion Program
- Employee Resource Groups (ERG)
Company Videos
Hear directly from employees about what it is like to work at TikTok.