Machine Learning Engineer - E-commerce - Seattle

$129,200 - $194,750/Yr

Tiktok - Seattle, WA

Full-time - Mid Level

Seattle, WA

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. As part of our E-commerce team, you will be at the forefront of connecting customers with excellent sellers and quality products through innovative solutions like E-commerce live-streaming and short videos. This role is crucial as we develop and enhance our E-commerce recommendation algorithms, focusing on improving user engagement and satisfaction. Our team consists of applied machine learning engineers and data scientists dedicated to creating impactful solutions that leverage large-scale machine learning to address real-world challenges in E-commerce. In this position, you will be responsible for designing and building optimization algorithm strategies for large-scale e-commerce recommendation systems, handling data pipelines that can process millions of transactions. You will create user interest models that analyze vast amounts of data to uncover latent interests, and you will develop predictive models for candidate generation and ranking, including Click Through Rate and Conversion Rate predictions. Your work will involve real-time data processing, feature engineering, and model optimization, ensuring that our algorithms are not only effective but also innovative. Additionally, you will design and build supporting tools to facilitate debugging and enhance the overall efficiency of our systems. This role requires a strong foundation in data structures and algorithms, proficiency in programming languages, and familiarity with machine learning frameworks. You will be part of a collaborative environment that values creativity and encourages growth, where every challenge is seen as an opportunity to learn and innovate.

Responsibilities

• Responsible for the build and design of optimization algorithm strategies for large-scale e-commerce recommendation algorithm pipeline or search engines.
• 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, including Click Through Rate and Conversion Rate prediction.
• Design and build supporting/debugging tools as needed.

Requirements

• Bachelor's degree in computer science or relevant areas.
• 3+ years of experience with a solid foundation in data structure and algorithm design, proficient in programming languages such as Python, Java, C++, R, etc.
• Familiar with common machine/deep learning, causal inference, and operational optimization algorithms, including classification, regression, clustering methods, as well as mathematical programming and heuristic algorithms.
• Familiar with at least one framework of TensorFlow / PyTorch / MXNet and its training and deployment details, as well as training acceleration methods such as mixed precision training and distributed training.
• Familiar with big data related frameworks and applications, with preference for those familiar with MR or Spark.

Nice-to-haves

• Experience in recommendation systems, online advertising, ranking, search, 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.

Benefits

• 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents.
• 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 like 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.