Machine Learning Engineer - E-commerce - San Jose

$136,800 - $280,000/Yr

Tiktok - San Jose, CA

Full-time - Mid Level

San Jose, 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. As part of our E-commerce team, you will be at the forefront of connecting customers to excellent sellers and quality products through innovative solutions like E-commerce live-streaming and short videos. This role is crucial as we develop and implement machine learning algorithms that enhance user engagement and satisfaction on TikTok Shop. Our team consists of applied machine learning engineers and data scientists dedicated to creating impactful solutions that drive business results. In this position, you will be responsible for designing and building optimization algorithms for large-scale e-commerce recommendation systems, handling data pipelines, and developing predictive models that improve user experience. You will work with large datasets, extracting relevant information to build user interest models and iterating on algorithms to ensure they meet the needs of our users. Your contributions will directly influence how users interact with our platform, making this a highly impactful role within the organization. We are looking for someone who is not only technically proficient but also passionate about applying machine learning to solve real-world problems in E-commerce. You will have the opportunity to collaborate with a diverse team, innovate, and grow in a fast-paced environment that values creativity and teamwork. At TikTok, we believe that every challenge is an opportunity to learn and grow, and we are excited to welcome someone who shares this vision.

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 building real-time data pipelines, feature engineering, model optimization and innovation.
• Design and build supporting/debugging tools as needed.

Requirements

• Bachelor's degree or above in computer science or relevant areas.
• 3+ years of experience with a solid foundation in data structure and algorithm design, and proficiency in programming languages such as Python, Java, C++, R, etc.
• Familiarity with common machine/deep learning, causal inference, and operational optimization algorithms, including classification, regression, clustering methods, as well as mathematical programming and heuristic algorithms.
• Familiarity 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.
• Familiarity 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, 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.