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Engineer Graduate: (Machine Learning Engineer - Local Services Search) - 2026 Start (PhD)

TikTok

Engineer Graduate: (Machine Learning Engineer - Local Services Search) - 2026 Start (PhD)

TikTok

San Jose, CA

·

On-site

·

Full-time

·

2mo ago

보상

$136,800 - $259,200

복지 및 혜택

Learning

Unlimited Pto

Healthcare

필수 스킬

SQL

Python

TensorFlow

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 Data-Search-Tik Tok-Local Services team enhances local services by improving user discovery of hospitality, dining, and leisure experiences while driving ecosystem growth. They leverage large-scale machine learning to refine search and recommendation systems, focusing on personalized relevance, CTR/CVR prediction, and optimized conversion efficiency for billions of users.

Responsibilities:

  1. Support the local video service business to enhance user discovery of life services such as hospitality, dining, and leisure.
  2. Improve the search experience in local services and promote ecosystem growth.
  3. Utilize large-scale machine learning techniques in search and recommendation scenarios with billions of users to: Improve user shopping experiences & Enhance conversion efficiency.
  4. Design and implement local services search algorithms across the full stack, including: Query analysis, relevance, recall, coarse ranking, fine ranking, and blended ranking. Personalized behavior modeling for relevance computation.
    CTR (Click-Through Rate) prediction, CVR (Conversion Rate) prediction. Vector recall and value blending.

Qualifications

Minimum Qualifications:

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  1. Excellent analytical and problem-solving skills.2. Strong foundation in machine learning and deep learning, with experience in: NLP (Natural Language Processing).Personalization.3. Exceptional coding skills with solid knowledge of data structures and algorithms.4. Proficiency in Linux development environments.

Preferred Qualifications1. Prior experience in search, recommendation, or advertisement algorithms.2. Familiarity with local life services and e-commerce businesses.

Job InformationFor 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.

Client-provided location(s): San Jose, CA

Job ID: Tik Tok-7515280811014523144

Employment Type: OTHER

Posted: 2025-06-15T04:22:05
Apply 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.

Apply on company site

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본사 위치

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기업 가치

리뷰

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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

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1개 리포트

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총 연봉

기본급

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주식

-

보너스

-

$273,000

$273,000

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