Tech Lead, Machine Learning Engineer, E-commerce Feed Recommendation

$224,000 - $410,000/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

As a Tech Lead, Machine Learning Engineer for E-commerce Feed Recommendation at TikTok, you will play a pivotal role in shaping the future of our interest-based E-commerce platform. This position is centered around developing large-scale recommendation algorithms that enhance the shopping experience for our users. TikTok Shop is not just another E-commerce platform; it offers a unique and personalized shopping experience through live-streaming and short videos, making the recommendation system crucial for connecting customers with high-quality products and sellers. In this role, you will be part of a dynamic team of applied machine learning engineers and research scientists dedicated to improving user engagement and satisfaction on TikTok. You will work on innovative algorithms and machine learning techniques that directly impact billions of users daily. Your contributions will help us tackle real-world problems in E-commerce and recommendation, driving significant business outcomes. You will be responsible for designing, developing, and iterating on predictive models that enhance our recommendation systems. This includes building real-time data pipelines, conducting feature engineering, and optimizing models for candidate generation and ranking. You will also analyze large datasets to extract relevant information and design algorithms that efficiently explore users' latent interests. Your work will involve addressing various E-commerce challenges, such as the cold start problem and traffic allocation, ensuring that our users have a seamless shopping experience. This position requires a blend of technical expertise, creativity, and a passion for machine learning and E-commerce. You will have the opportunity to lead projects, mentor junior engineers, and collaborate with cross-functional teams to drive impactful solutions that align with TikTok's mission to inspire creativity and bring joy.

Responsibilities

• Participate in building large-scale (10 million to 100 million) live-streaming and short video e-commerce recommendation algorithms and systems on TikTok.
• 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.
• 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 and develop various strategies using ML technology to improve user shopping experience, and resolve e-commerce business challenges, such as the cold start problem and traffic allocation.
• 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.
• 5 years of experience in applied machine learning, familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc.
• Experience in Deep Learning Tools such as tensorflow/pytorch.
• Experience with at least one programming language like C++/Python or equivalent.

Nice-to-haves

• 3 years of experience in recommendation system, online advertising, 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 etc.

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 like Health Care, Limited Purpose and Dependent Care.
• 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) 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 our EAP and Lyra.
• 401K company match, gym and cellphone service reimbursements.