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Research Scientist Graduate- CV/NLP/Multimodal LLM, Trust and Safety, San Jose - 2026 Start (BS/MS)

TikTok

Research Scientist Graduate- CV/NLP/Multimodal LLM, Trust and Safety, San Jose - 2026 Start (BS/MS)

TikTok

San Jose, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$118,657 - $259,200

Benefits & Perks

Competitive salary and equity package

Professional development budget

Parental leave

Generous paid time off and holidays

Equity

Learning

Parental Leave

Required Skills

TypeScript

React

Node.js

Responsibilities

The algorithm team is responsible for developing state-of-the-art computer vision, NLP and multimodality models and algorithms to protect our platform and users from the content and behaviors that violate community guidelines and related regulations. With the continuous efforts from our team, Tik Tok is able to provide the best user experience and bring joy to everyone in the world.

In our team, you will have the opportunity to participate in the development of the cutting-edge content understanding model to help improve the recognition ability of violated content in Tik Tok, and will also be responsible for optimizing our distributed model training framework continuously.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at Tik Tok.

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 Tik Tok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible.

Key Responsibilities

  • Develop computer vision model or multimodality model to recognize violation content in Tik Tok
  • Explore cutting-edge multimodal or computer vision large models (CLIP, COCA, ALBEF, BLIP, Flamingo, ViT-G, ViT-22B, EVA-enormous, etc)
  • Explore the application of LLM in our business scenarios, like pre-training, zero-shot/ few-shot learning, hard case mining, etc
  • Continuously optimize the training framework to better adapt to the training of large models

Qualifications

Minimum Qualifications

  • Master or Bachelor degree in computer science or a related technical discipline
  • Related Research Experience at least one of the following areas: computer vision, multimodality, LLM
  • Be proficient with at least one deep learning framework (e.g. Py Torch, Tensor Flow)
  • Have excellent analytical and problem-solving skills, logical thinking skills, communication and collaboration skills

Preferred Qualifications

  • Published papers in the top AI conferences or journals is a plus, including CVPR, ICCV, ECCV, NIPS, ICML, ICLR, TPAMI, IJCV, etc

Compensation

The base salary range for this position in the selected city is $118,657 - $259,200 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

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
  • 401(k) savings plan with company match
  • Paid parental leave
  • Short-term and long-term disability coverage
  • Life insurance
  • Wellbeing benefits
  • 10 paid holidays per year
  • 10 paid sick days per year
  • 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.

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:

  • Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues
  • Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems
  • Exercising sound judgment

Privacy

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

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About TikTok

TikTok

TikTok

Late Stage

A short-form video entertainment app and social network platform

10,001+

Employees

Los Angeles

Headquarters

$220B

Valuation

Reviews

3.1

3 reviews

Work Life Balance

1.5

Compensation

2.0

Culture

1.2

Career

1.8

Management

1.0

5%

Recommend to a Friend

Pros

Limited positive feedback available

Company size allows for potential opportunities

Technology platform experience

Cons

Mass layoffs and poor handling of terminations

Unprofessional management and HR behavior

Exposure to traumatic content without adequate support

Salary Ranges

52 data points

Mid/L4

Senior/L5

Mid/L4 · Applied AI Product Data Scientist

1 reports

$273,000

total / year

Base

$210,000

Stock

-

Bonus

-

$273,000

$273,000

Interview Experience

4 interviews

Difficulty

3.5

/ 5

Duration

21-35 weeks

Experience

Positive 0%

Neutral 25%

Negative 75%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Data Structures