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Senior Machine Learning Engineer (CV/NLP/Multimodal/LLM/Agent)-E-Commerce Government

TikTok

Senior Machine Learning Engineer (CV/NLP/Multimodal/LLM/Agent)-E-Commerce Government

TikTok

Seattle, WA

·

On-site

·

Full-time

·

1mo ago

Compensation

$177,688 - $341,734

Benefits & Perks

Wellness benefits

Annual team offsites

Top Tier compensation with equity

Learning and development stipend

Health, dental, and vision coverage

Flexible PTO policy

Required Skills

PyTorch

TensorFlow

SQL

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 e-commerce industry has seen tremendous growth in recent years and has become a hotly contested space amongst leading Internet companies, and its future growth cannot be underestimated. With millions of loyal users globally, we believe Tik Tok is an ideal platform to deliver a brand new and better e-commerce experience to our users. We aim to bring discovery, inspiration, and joy back to shopping by making Tik Tok the commerce channel of choice for merchants, creators, and affiliates.

With millions of loyal users globally, we believe Tik Tok is an ideal platform to deliver a brand new and better e-commerce experience to our users. We are looking for passionate and talented people to join our product and operations team, to build an e-commerce ecosystem that is innovative, secure and intuitive for our users and brands.

About the Team:

The Governance and Experience Algorithm team was established in September 2020 and its main job is to support the following businesses with the most advanced AI technology:

  • Combat any kinds of risks/violations issues in E-commerce scenarios.
  • Build a safe E-commerce ecosystem and improve platform service capabilities

Responsibilities:

  • Responsible for identifying algorithms for risk/violation/low-quality issues in e-commerce scenarios such as products, shopping cart short videos, and live streaming with products.
  • Responsible for mining and identifying algorithms to detect fraudulent behaviors and identify risky, violated, or low-quality merchants and creators.
  • Responsible for optimizing algorithms for large-scale brand libraries, products, and content deduplication/clustering.
  • Responsible for data construction, instruction fine-tuning, CoT, alignment, and other work for large models in the e-commerce domain, aiming for ultimate effect optimization in the e-commerce domain.
  • Responsible for exploring reinforcement learning and operational research algorithms in intelligent dispatching and intelligent audit scheduling to improve audit quality and efficiency.
  • Responsible the research and development of multi-agent tools, models, engines, and platforms to enhance automatic planning, generalized decision-making, and multimodal interaction capabilities in e-commerce scenarios. Deliver Agent-based solutions to address problems beyond the reach of existing methods and models, identify capability gaps in current models, and feed insights from real-world applications back into foundational model iteration.
  • Drive performance and stability optimization of Agent Systems, including but not limited to system resource utilization, environment interaction latency, and overall cost efficiency. Abstract and generalize capabilities from business requirements, define the platform roadmap, and build a stable, reliable Agent infrastructure.

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What You Will Do:

  • Optimize various basic algorithms such as NLP, vision, multimodal, search, graph, LLM, Agent etc. to provide support for governance business, explore cutting-edge technologies, and apply them to e-commerce business scenarios.
  • Streamline the optimization and iteration process for computer vision models in e-commerce settings, including fine-grained classification of product images, product object recognition, product subject recognition, feature extraction, logo detection, brand recognition, etc.
  • Optimize video classification, multimodal content mining, and multimodal content understanding of e-commerce short videos and live broadcasts, and optimize the e-commerce short video shopping experience.
  • Optimize the risk identification model related to text content in e-commerce scenarios, such as product copywriting, picture text, and voice descriptions.
  • Optimize the risk mining algorithm for comments, reports, and other public opinion content related to products/short videos/live broadcasts, and improve the platform governance effect.
  • Responsible for the research of large-scale multimodal (vision, speech, natural language, etc.) algorithms and their implementation in e-commerce scenarios.
  • Extract extensive data from various entities, such as content in e-commerce live broadcasts, products, merchants, and influencers. Model large-scale networks to support business scenarios like content understanding, multimodal representation, and community mining for problem-solving purposes.
  • Participate in the construction of a large-scale graph storage and graph learning platform, supporting the basic ability of graph learning with billions of nodes and edges.

Qualifications:

Minimum Qualifications:

  • Bachelor's degree or above in computer science or related field

  • Solid coding skills, ability to develop in a Linux environment, proficient in Python, Go, or C++

  • Solid foundation in data structures/algorithms, proficient in machine learning/deep learning theory, and rich practical experience

  • Familiar with 1+ areas in natural language processing, computer vision, multimodal, graph algorithms, search algorithms, text/data mining, and LLM

  • Preferred Qualifications

  • Excellent analytical and problem-solving skills, passionate about challenging problems

  • Good team spirit and strong communication skills

  • Experience in platform governance/audit/risk control/content security or overseas internet/e-commerce business is preferred

Job InformationFor Pay Transparency Compensation Description (annually)

The base salary range for this position in the selected city is $177688 - $341734 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): Seattle, WA

Job ID: Tik Tok-7595412683009394997

Employment Type: OTHER

Posted: 2026-01-20T19:49:26
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