TikTok

Interest-based E-commerce is a new and fast growing business that aims at connecting all customers' interests to excellent sellers and high quality products on TikTok Shop. Different from other traditional E-commerce platforms, Tiktok Shop provides customers with personalized and unique shopping experience through E-commerce live-streaming and E-commerce short videos.. We are a group of applied machine learning engineers and research scientists that focus on E-commerce video/live-streaming recommendations on the major traffic source of Tiktok ForU page, where we serve traffic for billions of users every single day.. Research and experiment with cutting-edge machine learning techniques, including NLP, computer vision, and information retrieval, to enhance recommendation accuracy and user satisfaction.. Familiar with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).. Strong first-author publications in top-tier machine learning, NLP, computer vision, or information retrieval conferences/journals (e.g., NeurIPS, ICML, CVPR, ACL, SIGIR, KDD, EMNLP).

engineer

Responsibilities TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo. Why Join Us Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible. Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day. To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always. At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve. Join us. Interest-based E-commerce is a new and fast growing business that aims at connecting all customers' interests to excellent sellers and high quality products on TikTok Shop. Different from other traditional E-commerce platforms, Tiktok Shop provides customers with personalized and unique shopping experience through E-commerce live-streaming and E-commerce short videos. The recommendation system plays an extremely important role in helping customers explore their shopping interests. We are a group of applied machine learning engineers and research scientists that focus on E-commerce video/live-streaming recommendations on the major traffic source of Tiktok ForU page, where we serve traffic for billions of users every single day. Our goal is to connect users with products they love, creating a seamless and engaging shopping journey. We utilize cutting-edge machine learning techniques to provide personalized product/video/live recommendations, boosting user satisfaction and driving e-commerce success. We are looking for talented research scientists to join our team in 2025, you will be instrumental in designing, implementing, and optimizing machine learning models that power our recommendation systems. You will collaborate with a team of skilled engineers and researchers to build scalable solutions that enhance the e-commerce experience for TikTok users. This role offers the chance to apply your research expertise to solve real-world problems and make a substantial impact on our growing e-commerce platform. Responsibilities 1. Develop, implement, and optimize machine learning models for personalized product/video/live recommendations. 2. Collaborate with cross-functional teams to gather requirements and integrate machine learning solutions into the e-commerce platform. 3. Conduct data analysis to uncover insights and drive model improvements. 4. Research and experiment with cutting-edge machine learning techniques, including NLP, computer vision, and information retrieval, to enhance recommendation accuracy and user satisfaction. 5. Evaluate and improve the performance of existing recommendation algorithms. Qualifications Minimum Qualifications: 1. PhD or equivalent degree in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field. 2. Strong understanding of machine learning algorithms and techniques, 3. Proficiency in programming languages such as Python, Java, or C++, Solid background in data analysis and statistical modeling. 4. Familiar with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). 5. Excellent problem-solving skills and the ability to think creatively and critically. Ability to work effectively in a collaborative team environment. Preferred Qualifications: 1. Strong first-author publications in top-tier machine learning, NLP, computer vision, or information retrieval conferences/journals (e.g., NeurIPS, ICML, CVPR, ACL, SIGIR, KDD, EMNLP). 2. Familiarity with deep learning techniques and neural network architectures. 3. Experience in e-commerce or related AI research domains. TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too. TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://shorturl.at/cdpT2 Job Information: 【For Pay Transparency】Compensation Description (annually) The base salary range for this position in the selected city is $137750 - $237500 annually.​Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.​Our company benefits are designed to convey company culture and values, to create an efficient and inspiring work environment, and to support our employees to give their best in both work and life. We offer the following benefits to eligible employees: ​We cover 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents and offer a Health Savings Account(HSA) with a company match. As well as Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans. In addition to Flexible Spending Account(FSA) Options like Health Care, Limited Purpose and Dependent Care. ​Our time off and leave plans are: 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 as well as 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability. ​We also provide generous benefits like mental and emotional health benefits through our EAP and Lyra. A 401K company match, gym and cellphone service reimbursements. The Company reserves the right to modify or change these benefits programs at any time, with or without notice.​For Los Angeles County (unincorporated) Candidates:​Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:​1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;​2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and​3. Exercising sound judgment.​

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