Machine Learning Engineer Intern (Recommendation) - 2023

Key Skills

C++, GoLang, Java Programming, Machine learning techniques, Python Programming, Quantitative models, Recommendation Systems, SQL

Job Description

Why Join Us

At TikTok, our people are humble, intelligent, compassionate and creative. We create to inspire - for you, for us, and for more than 1 billion users on our platform. We lead with curiosity and aim for the highest, never shying away from taking calculated risks and embracing ambiguity as it comes. Here, the opportunities are limitless for those who dare to pursue bold ideas that exist just beyond the boundary of possibility. Join us and make impact happen with a career at TikTok.

We are looking for talented individuals to join us for an internship in 2023. Internships at TikTok aim to offer students industry exposure and hands-on experience. Watch your ambitions become reality as your inspiration brings infinite opportunities at TikTok.

Successful candidates must be able to commit to one of the following internship cycles below: -

• Summer Internship - 08 May 2023 to 28 July 2023 (12 weeks)
• Off-cycle Internship - Starting 09 January 2023 or 14 August 2023

We will prioritize candidates who are able to commit in either internship period. Please state your availability clearly in your resume (Start date, End date).

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is firm and includes all TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis and we encourage you to apply early.

About the team

Our team works on large-scale recommendation systems for various offerings under TikTok and its affiliates, focusing on developing recommendation algorithms/models/strategies. We are committed to developing cutting-edge solutions for e-commerce recommendation systems.

Responsibilities

• Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in TikTok.
• Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.
• Design, develop, evaluate and iterate on predictive models for candidate generation and ranking(eg. Click Through Rate and Conversion Rate prediction) , including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation.
• Design and build supporting/debugging tools as needed.

Qualifications

• Undergraduate, or Postgraduate who is currently pursuing a degree/master in Computer Science, or a related technical major;
• Strong programming and problem-solving ability.
• Experience in applied machine learning, familiar with common machine learning and deep learning models. (K-means, LR, GBDT, FM, DNN, Transformer)
• Experience in Deep Learning Tools such as tensorflow/pytorch.

Preferred Qualifications

• Experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.
• Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc.

TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy.

If you have any questions, please reach out to us at apac-earlycareers@tiktok.com.