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Software Engineer in Machine Learning Infra - TikTok Recommendation Architecture

TikTok

Software Engineer in Machine Learning Infra - TikTok Recommendation Architecture

TikTok

Singapore

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Parental leave program

Top Tier compensation with equity

Wellness benefits

Learning and development stipend

Remote work flexibility

Required Skills

SQL

Airflow

Python

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

Tik Tok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. Tik Tok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, Jakarta, Seoul and Tokyo.

Why Join Us:

Creation is the core of Tik Tok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make Tik Tok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At Tik Tok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.

About The Team:

Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for our recommendation system to provide the most stable and best experience for our Tik Tok users. The team is responsible for system stability and high availability, online services and offline data flow performance optimization, solving system bottlenecks, reducing cost overhead, building data and service mid-platform, realizing flexible and scalable high-performance storage and computing systems.

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Responsibilities- Serving and training infra optimization of machine learning models- Build and maintain high performance online services for Tik Tok recommendation system- Build globalized large-scale recommendation system- Research, design, and develop computer and network software or specialised utility programs- Analyse user needs and develop software solutions, applying principles and techniques of computer science, engineering, and mathematical analysis- Update software, enhances existing software capabilities, and develops and direct software testing and validation procedures- Work with computer hardware engineers to integrate hardware and software systems and develop specifications and performance requirements Qualifications

  • Bachelor's degree or above, majoring in Computer Science, or related fields, with 3+ years of experience building scalable systems.
  • Experience at least one or two programming languages in Linux environment such as C/C++/golang;
  • Understand GPU hardware architecture, understand GPU software stack (CUDA, cuDNN), and have experience in GPU performance analysis;
  • Have experience in deep model inference/training, debugging, tuning, and familiar with model optimization tools such as TVM, MLIR, XLA;
  • Familiar with mainstream machine learning frameworks (e.g., Tensorflow, Pytorch, Mx Net);

Tik Tok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At Tik Tok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

Client-provided location(s): Singapore

Job ID: Tik Tok-7229162198592014647

Employment Type: OTHER

Posted: 2025-01-21T00:51:25
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

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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