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Machine Learning Engineer Graduate (Monetization Technology - TikTok Ads Creative & Ecosystem) - 2026 Start (BS/MS)

TikTok

Machine Learning Engineer Graduate (Monetization Technology - TikTok Ads Creative & Ecosystem) - 2026 Start (BS/MS)

TikTok

San Jose, CA

·

On-site

·

Full-time

·

2mo ago

보상

$118,657 - $259,200

복지 및 혜택

Equity

Healthcare

Parental Leave

Unlimited Pto

필수 스킬

Python

TensorFlow

PyTorch

About the Role

A "creative" is the ad (in the form of a short-form video) served to Tik Tok users, composed of video, background music, call-to-action card, post-click landing page, and other formats that get delivered to users. A quote goes "creativity is the soul of advertising", because a good ad creative is effective, yet difficult to produce, especially at the scale of Tik Tok advertising.

The Tik Tok Ads Creative & Ecosystem team's mission is to solve the above dilemma, by building industry-leading tech solutions for ads creative/landing page understanding, production/generation, and optimization, to inspire and empower advertisers, creators, and other 3rd parties in the ecosystem to create and deliver the best engaging creative experiences to the end users. Our work is at the core of Tik Tok and creator monetization. Examples of our team's work include Tik Tok video editor, AI-powered smart video generation (we are also exploring AIGC), and Tik Tok creative exchange (a creative marketplace to connect Tik Tok advertisers with creators or third-party creative agencies).

We are user/product oriented and dedicated to technical excellence. We aim to drive and lead the technology renovation in the ads tech and creative industry, powering products and driving values for our clients, creators, and the whole ecosystem.

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 early.

Responsibilities

  1. Apply algorithms to gain insights into advertisers, creators, and creatives, helping to improve the precision of match-making in the system.
  2. Assist in conducting online modeling on large-scale commercial traffic, optimizing how creatives are distributed within the recommendation and ads systems.
  3. Contribute to the development of strategies that optimize the allocation of both natural and ad traffic, aimed at increasing short-term and long-term value for advertisers and creators.

Qualifications

Minimum Qualifications

  1. Bachelor's degree or higher in Computer Science or a related technical field.
  2. Relevant development experience with expertise in machine learning (Rec Sys/NLP/CV/GE), and hands-on experience with recommendation systems, computational advertising, or operational planning algorithms.
  3. Strong foundation in data structures and algorithms, with proficiency in Python, C++, or Golang.
  4. Proven analytical and problem-solving abilities, with a passion for learning new technologies.
  5. Strong team player with excellent communication skills and experience in project management.

Preferred Qualifications

  1. Experience with large-scale machine learning systems or cloud-based platforms (e.g., AWS, Google Cloud, Azure).
  2. Knowledge of advanced machine learning techniques such as deep learning or reinforcement learning.
  3. Familiarity with A/B testing and performance optimization in recommendation systems and advertising algorithms.
  4. Demonstrated ability to drive innovation and business growth through technical leadership and strategic thinking.

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, 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:

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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모의 지원자 수

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TikTok 소개

TikTok

TikTok

Late Stage

A short-form video entertainment app and social network platform

10,001+

직원 수

Los Angeles

본사 위치

$220B

기업 가치

리뷰

3.8

10개 리뷰

워라밸

2.8

보상

3.7

문화

4.1

커리어

3.2

경영진

2.9

68%

친구에게 추천

장점

Great team dynamics and support

Innovative and creative culture

Good learning opportunities

단점

Work-life balance challenges

Fast-paced and stressful environment

High expectations and tight deadlines

연봉 정보

49개 데이터

Senior/L5

Senior/L5 · ACCESS ASSURANCE LEAD USDS

1개 리포트

$331,500

총 연봉

기본급

$255,000

주식

-

보너스

-

$331,500

$331,500

면접 경험

2개 면접

난이도

4.0

/ 5

소요 기간

21-35주

경험

긍정 0%

보통 0%

부정 100%

면접 과정

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Behavioral Interview

5

Final Round

6

Offer

자주 나오는 질문

Coding/Algorithm

Behavioral/STAR

Technical Knowledge

Culture Fit