Senior Machine Learning Engineer, Recommendations - USDS

$177,688 - $341,700/Yr

Tiktok - Seattle, WA

Full-time - Mid Level

Seattle, WA

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

The position involves working as part of the U.S. Data Security (USDS) team at TikTok, focusing on developing large-scale recommendation algorithms and systems to enhance user engagement and satisfaction. The role emphasizes the application of machine learning techniques to solve real-world problems, contributing to TikTok's mission of inspiring creativity and bringing joy to users. The team operates in a hybrid work environment, requiring in-office presence three days a week.

Responsibilities

• Participate in building large-scale 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 data, and design algorithms to explore users' latent interests efficiently.
• Design, develop, evaluate, and iterate on predictive models for candidate generation and ranking, including building real-time data pipelines, feature engineering, model optimization, and innovation.
• Design and build supporting/debugging tools as needed.

Requirements

• Bachelor's degree or higher in Computer Science or related fields.
• Strong programming and problem-solving ability.
• Experience in applied machine learning, familiar with algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep.
• Experience in Deep Learning Tools such as TensorFlow/PyTorch.
• Experience with at least one programming language like C++/Python or equivalent.

Nice-to-haves

• Experience in recommendation systems, 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.

Benefits

• 100% premium coverage for employee medical insurance, approximately 75% 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.
• Flexible Spending Account (FSA) options for Health Care, Limited Purpose, and Dependent Care.
• 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) and 10 paid sick days per year.
• 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.
• Mental and emotional health benefits through EAP and Lyra.
• 401K company match, gym, and cellphone service reimbursements.