Machine Learning Engineer, E-commerce Feed Recommendation

Summary

TikTok is the leading destination for short-form mobile video, and they are seeking a Machine Learning Engineer for their E-commerce Feed Recommendation team. The role involves developing algorithms and systems to enhance user engagement and satisfaction through personalized shopping experiences.

Responsibilities

• Participate in building large-scale (10 million to 100 million) live-streaming and short video e-commerce recommendation algorithms and systems on TikTok
• 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
• 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 and develop various strategies using ML technology to improve user shopping experience, and resolve e-commerce business challenges, such as the cold start problem and traffic allocation
• Design and build supporting/debugging tools as needed

Skills

• Bachelor's degree or higher in Computer Science or related fields
• Strong programming and problem-solving ability
• 1 year 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
• 2 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, 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

Qualifications

Must Haves

• Bachelor's degree or higher in Computer Science or related fields
• Strong programming and problem-solving ability
• 1 year 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

Nice to Haves

• 2 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, 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

Benefits

• Employees have day one access to medical, dental, and vision insurance
• A 401(k) savings plan with company match
• Paid parental leave
• Short-term and long-term disability coverage
• Life insurance
• Wellbeing benefits
• 10 paid holidays per year
• 10 paid sick days per year
• 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)