Machine Learning Engineer Graduate (Search Ads) - 2027 Start

Description

The Search Ads team constantly pushes the boundaries of general search engine monetization across our apps, including TikTok, TopBuzz, BuzzVideo, and more, building a globally leading Search Ads monetization system. At the Search Ads team, you will have the chance to work on large-scale distributed storage and architecture, NLP, Rank, and IR related problems. You will be also deeply involved in the innovation and optimization of our Ad format, creative display, and the ROI of ads delivery.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to 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 you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities:
- Participate in the development of a large-scale Ads system
- Responsible for relevance model and strategy optimization, such as semantic matching models, active learning, text/photo/video multi-model, ranking strategy, etc
- Participate in the development and iteration of Ads algorithms by using Machine Learning.
- Work on NLP (Natural Language Processing) capability improvement and query understanding, such as query classification, seq2seq, NER (Named Entity Recognition), knowledge graph, bidword optimization, etc
- Work on CTR/CVR model estimation accuracy, data analysis, modeling, feature engineering
- Research and develop Ads pacing algorithms, ads traffic control, etc
- Partner with product managers and product strategy & operation team to define product strategy and features

Requirements

Minimum Qualifications:
- Individuals who are completing or have recently completed 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, etc
- Ability to think critically and to formulate solutions to problems in a clear and concise way.

Preferred Qualifications:
- Familiar with Ads system, recommendation, searching, ranking, etc.