E-commerce Recommendation Algorithms Engineer
1 week ago
TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy to our users.
We are a group of applied machine learning engineers and data scientists that focus on E-commerce recommendations. We develop innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions.
As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Responsibilities- Design and build large-scale e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, and short video recommendations.
- 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.
- Develop predictive models for candidate generation and ranking, including building real-time data pipelines, feature engineering, model optimization, and innovation.
- Support the production of scalable and optimized AI/machine learning (ML) models.
- Final year or recent PhD graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
- Strong programming and problem-solving ability.
- Experience in applied machine learning, familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc.
- Experience in Deep Learning Tools such as tensorflow/pytorch.
Yoga and fitness, stock options, positive team atmosphere, career growth opportunity, paid leave, flat organization, 100+ mil users, industry experts, competitive compensation, flexible hours.
OthersOur platform connects people from across the globe and so does our workplace. At TikTok, we strive to do great things with great people, leading with curiosity, humility, and a desire to make impact in a rapidly growing tech company.
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