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Machine Learning Engineer Graduate (Search Ads Technology) - 2026 Start (BS/MS)

TikTok

Machine Learning Engineer Graduate (Search Ads Technology) - 2026 Start (BS/MS)

TikTok

San Jose, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$118,657 - $187,200

Benefits & Perks

Remote work flexibility

Health, dental, and vision coverage

Wellness benefits

Flexible PTO policy

Required Skills

SQL

Python

TensorFlow

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Tik Tok

Machine Learning Engineer Graduate (Search Ads Technology) - 2026 Start (BS/MS)

3+ months ago• San Jose, CA
Viewed on February 1, 2026
Apply on company site

About Us

Tik Tok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.

  • Size: 5001-10000 employees
  • Industry: Entertainment & Gaming, Social Media, Technology

View Company Profile:

Responsibilities:

"The Search Ads team constantly pushes the boundaries of general search engine monetization across our apps, including Tik Tok, Top Buzz, Buzz Video, and more, building a globally leading Search Ads monetization system. At the Search Ads team, you will have the chance to work on large-scale distributed storage and architecture, NLP, Rank, and IR related problems. You will be also deeply involved in the innovation and optimization of our Ad format, creative display, and the ROI of ads delivery.

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 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 resumes.

Applications will be reviewed on a rolling basis. We encourage you to apply early.

  • Key Responsibilities
  • Participate in the development of a large-scale Ads system
  • Responsible for relevance model and strategy optimization, such as semantic matching models, active learning, text/photo/video multi-model, ranking strategy, etc
  • Participate in the development and iteration of Ads algorithms by using Machine Learning.
  • Work on NLP (Natural Language Processing) capability improvement and query understanding, such as query classification, seq2seq, NER (Named Entity Recognition), knowledge graph, bidword optimization, etc
  • Work on CTR/CVR model estimation accuracy, data analysis, modeling, feature engineering
  • Research and develop Ads pacing algorithms, ads traffic control, etc
  • Partner with product managers and product strategy & operation team to define product strategy and features

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By signing up, you agree to our Qualifications

Minimum Qualifications:

  • BS/MS degree in Computer Science, Computer Engineering, or other relevant majors.
  • Experience with one or more general purpose programming languages including but not limited to: Go, C/C++, Python
  • Experience with one or more of the following: Machine Learning, Deep Learning, NLP, ranking systems, recommendation systems
  • Solid communication and collaboration skills with the ability to work effectively with internal teams in a cross-functional environment

Preferred Qualifications:

  • Experience in and a good understanding of one of the following domains: Search, Ads, Recommendation, Monetization Products, Shopping Products.

Job Information:

For Pay Transparency Compensation Description (annually)

The base salary range for this position in the selected city is $118657 - $187200 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.

Client-provided location(s): San Jose, CAJob ID: Tik Tok-7532011065635588370Employment Type: OTHERPosted: 2025-07-30T00:42:01Apply on company site

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 Tik Tok.
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Next Up Tik Tok Client Provided Video 101:20

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  • 02:18Working at Tik Tok- Get Ready With Ali01:20Tik Tok Client Provided Video 100:33Client Provided Video 2 - Tik Tok02:07Working at Tik Tok
  • Limitless Possibilities01:41Working at Tik Tok
  • Women's Community01:31Working at Tik Tok
  • Women's Empowerment01:45Working At Tik Tok
  • BLXCK01:27Working at Tik Tok
  • Diversity, Equity and Inclusion with BLXCK
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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