Machine Learning Engineer, Content Understanding

Responsibilities

TikTok's immersive experience, global presence, and high engagement makes it the ideal destination for brands, big and small, to showcase their unique identity, connect with their consumers, and build strong lasting relationships over time. Our Brand Ads team focuses on enabling brands to grow and succeed on TikTok by creating cutting-edge monetization products that empowers users, creators, and advertisers.

The Brand Ads Team builds technologies that unlock business growth potential. This team owns several ads products: reservation ads, auction ads, and innovative content ads that enables advertisers and users to foster more awareness of their brand to attain their business goals. We work on the end-to-end ads delivery tech stack, including ads bidding, ranking, and forecasting.

We are looking for seasoned engineers that have strong problem solving skills and algorithm understanding to build and manage systems with high performance, scalability, and availability. You will have the opportunity to partner closely with a globalized engineering and product teams in a high-impact and fast-paced environment.

What You'll Do:
- Participate in the development of a large-scale Ads system.
- Responsible for the development of state-of-the-art applied machine learning projects.
- Own key targeting components or strategies in the TikTok ads monetization ecosystem.
- Work with product and business teams on product vision.

Qualifications

Minimum Qualifications:
- Experience in and good theoretical grounding in machine learning concepts and techniques.
- Proven experience in multimodal content understanding, with expertise in large language models (LLMs) and familiarity with cutting-edge progress in the field.
- Strong technical foundation in at least one major deep learning framework (e.g., PyTorch, TensorFlow).
- Proactive mindset, strong sense of ownership, excellent communication skills, and ability to collaborate across teams.

Preferred Qualifications:
- Hands-on experience deploying content understanding solutions in search, advertising, recommendation, or related domains.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $162000 - $387600 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.

Responsibilities

Responsibilities

TikTok's immersive experience, global presence, and high engagement makes it the ideal destination for brands, big and small, to showcase their unique identity, connect with their consumers, and build strong lasting relationships over time. Our Brand Ads team focuses on enabling brands to grow and succeed on TikTok by creating cutting-edge monetization products that empowers users, creators, and advertisers.

The Brand Ads Team builds technologies that unlock business growth potential. This team owns several ads products: reservation ads, auction ads, and innovative content ads that enables advertisers and users to foster more awareness of their brand to attain their business goals. We work on the end-to-end ads delivery tech stack, including ads bidding, ranking, and forecasting.

We are looking for seasoned engineers that have strong problem solving skills and algorithm understanding to build and manage systems with high performance, scalability, and availability. You will have the opportunity to partner closely with a globalized engineering and product teams in a high-impact and fast-paced environment.

What You'll Do:
- Participate in the development of a large-scale Ads system.
- Responsible for the development of state-of-the-art applied machine learning projects.
- Own key targeting components or strategies in the TikTok ads monetization ecosystem.
- Work with product and business teams on product vision.

Qualifications

Qualifications

Minimum Qualifications:
- Experience in and good theoretical grounding in machine learning concepts and techniques.
- Proven experience in multimodal content understanding, with expertise in large language models (LLMs) and familiarity with cutting-edge progress in the field.
- Strong technical foundation in at least one major deep learning framework (e.g., PyTorch, TensorFlow).
- Proactive mindset, strong sense of ownership, excellent communication skills, and ability to collaborate across teams.

Preferred Qualifications:
- Hands-on experience deploying content understanding solutions in search, advertising, recommendation, or related domains.