Machine Learning Engineer Graduate (Search Ads)
TikTok
About the Role
The Search Ads team focuses on the monetization of general search engines across applications like TikTok, TopBuzz, and BuzzVideo, aiming to build a globally leading Search Ads monetization system. This role offers the opportunity to work on large-scale distributed storage and architecture, NLP, Rank, and IR related problems. You will be deeply involved in innovating and optimizing Ad formats, creative display, and the ROI of ad delivery. As a graduate, you will have opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Key Responsibilities
- Participate in the development of a large-scale Ads system.
- Optimize relevance models and strategies, including semantic matching, active learning, text/photo/video multi-model, and ranking strategies.
- Participate in the development and iteration of Ad algorithms using Machine Learning.
- Improve NLP (Natural Language Processing) capabilities and query understanding, including query classification, seq2seq, NER (Named Entity Recognition), knowledge graph, and bidword optimization.
- Work on CTR/CVR model estimation accuracy, data analysis, modeling, and feature engineering.
- Research and develop Ads pacing algorithms and ad traffic control.
- Partner with product managers and the product strategy & operation team to define product strategy and features.
Requirements & Tech Stack
- Completion or recent completion of a Bachelor's or above degree in Computer Science, Software Engineering, Computer Engineering, or a related technical discipline.
- Experience in and good theoretical grounding in machine learning concepts and techniques.
- Excellent programming, debugging, and optimization skills in one or more general-purpose programming languages, including but not limited to: Go, C/C++, Python.
- Experience in one or more of the following frameworks: Tensorflow/PyTorch/MXNet.
- Ability to think critically and formulate clear, concise solutions to problems.
Preferred Qualifications
- Familiarity with Ad systems, recommendation, searching, and ranking.
Important Notes
- Successful candidates must commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.
- Candidates can apply to a maximum of two positions and will be considered for jobs in the order of application.
- Applications will be reviewed on a rolling basis; early application is encouraged.