TikTok
Machine Learning Engineer, E-commerce Feed Recommendation
TikTok, San Jose, California, United States, 95199
Responsibilities
TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Mumbai, Singapore, Jakarta, Seoul and Tokyo.
Why Join UsCreation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible. Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day. To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
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 (e.g., 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.
QualificationsBachelor's degree or higher in Computer Science or related fields.Strong programming and problem-solving ability.3 years+ of 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.Experience with at least one programming language like C++/Python or equivalent.
Preferred Qualifications:3 years+ of experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.Publications at KDD, NeurIPS, 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.
Job Information:Compensation Description (annually)The base salary range for this position in the selected city is $126,000 - $221,760 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.Our company benefits are designed to convey company culture and values, to create an efficient and inspiring work environment, and to support our employees to give their best in both work and life. We offer the following benefits to eligible employees:100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents, and a Health Savings Account (HSA) with a company match.Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans.10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) and 10 paid sick days per year as well as 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.Mental and emotional health benefits through our EAP and Lyra.A 401K company match, gym and cellphone service reimbursements.The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
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TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Mumbai, Singapore, Jakarta, Seoul and Tokyo.
Why Join UsCreation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible. Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day. To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
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 (e.g., 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.
QualificationsBachelor's degree or higher in Computer Science or related fields.Strong programming and problem-solving ability.3 years+ of 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.Experience with at least one programming language like C++/Python or equivalent.
Preferred Qualifications:3 years+ of experience in recommendation system, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.Publications at KDD, NeurIPS, 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.
Job Information:Compensation Description (annually)The base salary range for this position in the selected city is $126,000 - $221,760 annually. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.Our company benefits are designed to convey company culture and values, to create an efficient and inspiring work environment, and to support our employees to give their best in both work and life. We offer the following benefits to eligible employees:100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents, and a Health Savings Account (HSA) with a company match.Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans.10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) and 10 paid sick days per year as well as 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.Mental and emotional health benefits through our EAP and Lyra.A 401K company match, gym and cellphone service reimbursements.The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
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