Senior Machine Learning Engineer - E-commerce Risk Control

$184,300 - $337,250/Yr

Tiktok - Seattle, WA

Full-time - Senior

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, with a mission to inspire creativity and bring joy. The E-Commerce Risk Control (ECRC) team is dedicated to protecting TikTok e-commerce users, including buyers, sellers, and creators, by ensuring that TikTok e-commerce is the safest and most trusted platform for online transactions. This involves securing the integrity of the e-commerce ecosystem and providing a safe shopping experience. The ECRC team works to prevent and detect risks on TikTok's e-commerce platforms, such as TikTok Shop and Fanno, addressing various business risk areas including account integrity, incentive abuse, malicious activities, and information leakage. As a Senior Machine Learning Engineer, you will be responsible for inventing, implementing, and deploying state-of-the-art machine learning algorithms to mitigate business risks associated with TikTok products and platforms. You will build prototypes, explore new solutions, and conduct experiments to validate hypotheses, while collaborating with cross-functional teams from diverse backgrounds to enhance automation processes. Your role will also involve developing efficient data querying infrastructure for both offline and online analysis, defining risk control measurements, and quantifying risk-related metrics. Effective communication of results through technical documentation, visualizations, and presentations will be essential in this position.

Responsibilities

• Invent, implement, and deploy state of the art machine learning algorithms to respond to and mitigate business risks in TikTok products/platforms.
• Build prototypes and explore conceptually new solutions, define and conduct experiments to validate/reject hypotheses, and communicate insights and recommendations to Product and Tech teams.
• Collaborate with cross-functional teams from multidisciplinary science, engineering, and business backgrounds to enhance current automation processes.
• Develop efficient data querying infrastructure for both offline and online analysis, uncover evolving attack motion, identify weaknesses and opportunities in risk defense solutions, and explore new space from the discoveries.
• Define risk control measurements, quantify, generalize, and monitor risk-related business and operational metrics, and align risk teams and their stakeholders on risk control numeric goals.

Requirements

• Bachelor's or Master's degree in Computer Science, Mathematics, Machine Learning, or other relevant STEM majors.
• 4+ years of hands-on experience in building and delivering machine learning models for large-scale projects.
• Track record of developing and implementing models and visualizations using programming and scripting languages such as Scala, Python, R, Ruby, and/or Matlab.
• Experience using various forecasting, machine learning, and statistical tools and communicating results, plans, and/or risks clearly.
• Ability to think creatively and solve problems.

Nice-to-haves

• A PhD in Computer Science, Machine Learning, Statistics, Operations Research, or a relevant field.
• Industry experience in predictive modeling and analysis.
• Experience collaborating with product, operations, and engineering teams is a plus.
• Excellent analytical and communication skills and ability to influence stakeholders.
• Experience in e-commerce or online companies in fraud/risk control functions.

Benefits

• 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.
• 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.