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Machine Learning Engineer, TikTok Core Feed Recommendation

TikTok

Machine Learning Engineer, TikTok Core Feed Recommendation

TikTok

San Jose, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$136,800 - $259,200

Benefits & Perks

Parental leave program

Health, dental, and vision coverage

Learning and development stipend

Top Tier compensation with equity

Required Skills

TensorFlow

Airflow

Python

Machine Learning Engineer, Tik Tok Core Feed Recommendation

3+ months ago• San Jose, CA

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

Responsibilities1. Research and develop large-scale recommender systems for personalized, engaging user experiences, focusing on scalability, accuracy, and performance.
2. Apply advanced machine learning and deep learning techniques to optimize recommendation algorithms for Tik Tok's diverse user base.
3. Manage the end-to-end lifecycle of recommender models, from training and fine-tuning to deployment, monitoring, and continuous improvement.
4. Analyze complex data to uncover user preferences, behaviors, and trends, driving personalization and enhancing Tik Tok's recommendation capabilities.
5. Collaborate with cross-functional teams (infrastructure, product, research, etc.) to design and implement innovative solutions that improve the relevance and diversity of Tik Tok recommendations.

Qualifications

Minimum Qualifications:

  1. Ph.D. or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
  2. Experience in one or more areas of recommender systems, machine learning, computer vision, or natural language processing.
  3. Proficiency in programming skills, solid foundation in data structures and algorithms.
  4. Strong familiarity with deep learning architectures such as transformers, CNNs, RNNs, LSTMs, etc.
  5. Excellent analytical and problem-solving skills, with the ability to collaborate effectively in cross-functional teams.

Preferred Qualifications:

  1. Ph.D. in Computer Science, Electrical Engineering, or related fields.

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  1. Experience in building large-scale recommender systems that handle vast, diverse datasets and complex user interactions.
  2. Publications in top-tier venues such as Rec Sys, SIGGRAPH, CVPR, ICCV, ICML, NeurIPS, ICLR, or similar conferences/journals.

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-7343779888137029915

Employment Type: OTHER

Posted: 2024-11-21T12:48:14
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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

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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