Machine Learning Engineer, Recommendations - USDS

$116,000 - $250,000/Yr

Tiktok - Mountain View, CA

Full-time - Mid Level

Mountain View, CA

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

About the position

TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. U.S. Data Security (USDS) is a subsidiary of TikTok in the U.S., created to enhance focus and governance on our data protection policies and content assurance protocols to ensure the safety of U.S. users. Our commitment is to provide oversight and protection of the TikTok platform and U.S. user data, allowing millions of Americans to continue using TikTok for learning, earning, creative expression, and entertainment. The teams within USDS that deliver on this commitment span across Trust & Safety, Security & Privacy, Engineering, User & Product Ops, Corporate Functions, and more. As a Machine Learning Engineer in the Recommendations team, you will be part of a group of applied machine learning engineers and data scientists focused on general feed recommendations and E-commerce recommendations. Your role will involve developing innovative algorithms and techniques to enhance user engagement and satisfaction, transforming creative ideas into impactful business solutions. You will have the opportunity to apply large-scale machine learning to solve various real-world problems, contributing to the overall mission of TikTok. In this position, you will participate in building large-scale recommendation algorithms and systems, including commodity recommendations, live stream recommendations, and short video recommendations. You will also be responsible for building user interest models, analyzing large datasets, and designing algorithms to efficiently explore users' latent interests. Additionally, you will design, develop, evaluate, and iterate on predictive models for candidate generation and ranking, including building real-time data pipelines and optimizing models. This role requires collaboration and cross-functional partnerships, and you will follow a hybrid work schedule, working in the office three days a week or as directed by your manager.

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 and analyze large amounts of data to design algorithms that explore users' latent interests efficiently.
• Design, develop, evaluate, and iterate on predictive models for candidate generation and ranking, including Click Through Rate and Conversion Rate prediction.
• Build real-time data pipelines, perform feature engineering, and optimize models for 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 or PyTorch.
• Experience with at least one programming language like C++ or Python.

Nice-to-haves

• Experience in recommendation systems, online advertising, information retrieval, natural language processing, machine learning, or large-scale data mining.
• Publications at KDD, NeurIPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS, 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 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.