Machine Learning Engineer - Search Ads

TikTok is seeking a Machine Learning Engineer to join the Search Ads team in San Jose, on site. This role focuses on building large-scale ads systems that leverage NLP, ranking, and optimization across TikTok apps such as TikTok, TopBuzz, BuzzVideo, and others, delivering scalable ML-powered advertising capabilities.

Responsibilities

• Contribute to the design and deployment of a large-scale Ads system.
• Drive relevance model development and strategy optimization, including semantic matching models, active learning, multi-model text/photo/video processing, and ranking strategies.
• Develop and iterate Ads algorithms through machine learning techniques.
• Advance NLP capability and query understanding, such as query classification, seq2seq models, Named Entity Recognition, knowledge graphs, and bidword optimization.
• Improve CTR and CVR model estimation accuracy through data analysis, modeling, and feature engineering.
• Research and implement Ads pacing algorithms and traffic control mechanisms.
• Collaborate with product managers and the product strategy and operations team to define product strategy and features.

Requirements

• BS degree in Computer Science, Computer Engineering or other relevant majors.
• Excellent programming, debugging, and optimization skills in general purpose programming languages.
• Ability to think critically and formulate solutions to problems in a clear and concise way.

Technologies

• Go
• C/C++
• Python

Benefits

• Base salary range: $156,000 - $316,800 annually
• Potential discretionary bonuses/incentives
• Restricted stock units
• Medical, dental, and vision insurance
• 401(k) savings plan with company match
• Paid parental leave
• Short-term and long-term disability coverage
• Life insurance
• Wellbeing benefits
• 10 paid holidays per year
• 10 paid sick days per year
• 17 days of Paid Personal Time

Los Angeles County (Unincorporated) Candidates

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
2. Adequately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
3. Exercising sound judgment.