Senior Machine Learning Engineer, Search - Local Services Team

TikTok Inc.; San Jose (CA); On-site; USD 218,000 - 388,000; Full time

Benefits offered by this job

Health insurance

401(k) with company match

Paid parental leave

Disability coverage

Job summary

TikTok Inc. is seeking a Senior ML Engineer to advance local services search and recommendation systems, enabling discovery of hospitality, dining, and leisure experiences.

You will work with large-scale ML techniques to improve relevance, CTR/CVR, and conversion efficiency for billions of users. You will design end-to-end ranking pipelines, implement full-stack search solutions, and model personalized behavior to optimize user engagement.

Qualifications

• Excellent analytical and problem-solving skills.
• Strong foundation in machine learning and deep learning, with experience in NLP and personalization.
• Exceptional coding skills with solid knowledge of data structures and algorithms.
• Proficiency in Linux development environments.

Responsibilities

• Support the local video service business to enhance user discovery of life services such as hospitality, dining, and leisure.
• Improve the search experience in local services and promote ecosystem growth.
• Utilize large-scale machine learning techniques in search and recommendation scenarios with billions of users to: Improve user shopping experiences and Enhance conversion efficiency.
• Design and implement local services search algorithms across the full stack, including: Query analysis, relevance, recall, coarse ranking, fine ranking, and blended ranking. Personalization for relevance computation. CTR prediction, CVR prediction. Vector recall and value blending.

Skills

Analytical skills

Machine learning

Deep learning

NLP

Personalization

Coding

Data structures

Algorithms

Linux development

Job description

Responsibilities

About the Team: The Data-Search-TikTok-Local Services team enhances local services by improving user discovery of hospitality, dining, and leisure experiences while driving ecosystem growth. They leverage large-scale machine learning to refine search and recommendation systems, focusing on personalized relevance, CTR/CVR prediction, and optimized conversion efficiency for billions of users.

Responsibilities:

1. Support the local video service business to enhance user discovery of life services such as hospitality, dining, and leisure.
2. Improve the search experience in local services and promote ecosystem growth.
3. Utilize large-scale machine learning techniques in search and recommendation scenarios with billions of users to: Improve user shopping experiences & Enhance conversion efficiency.
4. Design and implement local services search algorithms across the full stack, including: Query analysis, relevance, recall, coarse ranking, fine ranking, and blended ranking. Personalized behavior modeling for relevance computation. CTR (Click-Through Rate) prediction, CVR (Conversion Rate) prediction. Vector recall and value blending.

Qualifications

Minimum Qualifications

1. Excellent analytical and problem-solving skills.
2. Strong foundation in machine learning and deep learning, with experience in: NLP (Natural Language Processing). Personalization.
3. Exceptional coding skills with solid knowledge of data structures and algorithms.
4. Proficiency in Linux development environments.

Preferred Qualifications

1. Prior experience in search, recommendation, or advertisement algorithms.
2. Familiarity with local life services and e-commerce businesses.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $218400 - $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

About the Team: The Data-Search-TikTok-Local Services team enhances local services by improving user discovery of hospitality, dining, and leisure experiences while driving ecosystem growth. They leverage large-scale machine learning to refine search and recommendation systems, focusing on personalized relevance, CTR/CVR prediction, and optimized conversion efficiency for billions of users.

Responsibilities:

1. Support the local video service business to enhance user discovery of life services such as hospitality, dining, and leisure.
2. Improve the search experience in local services and promote ecosystem growth.
3. Utilize large-scale machine learning techniques in search and recommendation scenarios with billions of users to: Improve user shopping experiences & Enhance conversion efficiency.
4. Design and implement local services search algorithms across the full stack, including: Query analysis, relevance, recall, coarse ranking, fine ranking, and blended ranking. Personalized behavior modeling for relevance computation. CTR (Click-Through Rate) prediction, CVR (Conversion Rate) prediction. Vector recall and value blending.

Qualifications

Minimum Qualifications

1. Excellent analytical and problem-solving skills.
2. Strong foundation in machine learning and deep learning, with experience in: NLP (Natural Language Processing). Personalization.
3. Exceptional coding skills with solid knowledge of data structures and algorithms.
4. Proficiency in Linux development environments.

Preferred Qualifications

1. Prior experience in search, recommendation, or advertisement algorithms.
2. Familiarity with local life services and e-commerce businesses.