refresh

Trending Companies

Trending

Jobs

JobsTikTok

Machine Learning Engineer Graduate (Recommendations, USDS) - 2025 Start (MS)

TikTok

Machine Learning Engineer Graduate (Recommendations, USDS) - 2025 Start (MS)

TikTok

San Jose, CA

·

On-site

·

Full-time

·

1mo ago

Compensation

$118,657 - $187,200

Benefits & Perks

Flexible PTO policy

Parental leave program

Health, dental, and vision coverage

Learning and development stipend

Top Tier compensation with equity

Remote work flexibility

Required Skills

PyTorch

TensorFlow

Apache Spark

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

About the team
We are a group of applied machine learning engineers and data scientists that focus on general feed recommendations and E-commerce recommendations. We are developing innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested and excited in applying large scale machine learning to solve various real-world problems.

What you will do:

  • Participate in building large-scale (10 million to 100 million) recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in Tik Tok.
  • Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
  • Design, develop, evaluate and iterate on predictive models for candidate generation and ranking(eg. Click Through Rate and Conversion Rate prediction) , including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation.
  • Design and build supporting/debugging tools as needed.

In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.

Qualifications

  • Minimum Qualifications

  • PhD or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline.

  • 0-1 years of experience in machine learning, deep learning, data mining, or artificial intelligence.

  • Proficient in programming languages such as Python, C++, Java, or similar.

  • Preferred Qualifications

  • Deep understanding of recommendation algorithms and personalization systems.

  • Excellent problem-solving and analytical skills.

  • Strong ability to communicate complex ideas effectively to both technical and non-technical audiences.

Email Address

Send me The Muse newsletters for the best in career advice and job search tips.

Get jobs!

  • Experience with reinforcement learning techniques.
  • Proven modeling/algorithms competition records on Kaggle or top conferences' challenges.
  • Proven programming competition records on ICPC, IOI or USACO.
  • Experience working with recommendation systems, computational advertising, search engine, E-commerce recommendation systems.
  • Publications in machine learning or related conferences or journals are highly desirable.

Job InformationFor 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, CA

Job ID: Tik Tok-7497079736377428242

Employment Type: OTHER

Posted: 2025-04-26T13:08:22
Search all jobs

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.

Search all jobs

Similar Jobs

Suggested Searches

mid jobsTikTok jobsAll jobs

Search Additional Jobs

Machine Learning Engineer Graduate Jobs in San Jose, CAJobs in San Jose, CA

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

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