Deep Learning Engineer, TikTok e-Commerce – 2024 Start Undefined

TikTok will be prioritizing applicants who have a current right to work in Singapore, and do not require TikTok’s sponsorship of a visa. TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Singapore, 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. About the Team Relying on TikTok’s global e-commerce scene, the team is committed to optimizing TikTok’s global e-commerce logistics fulfillment services through technologies such as machine learning, deep learning, and operational research optimization. Externally, it provides cheap, fast, high-quality logistics services that meet different needs for global consumers and merchants; internally, it builds an intelligent logistics system to save costs, save time, improve efficiency, and improve stability for the fulfillment of orders. The intelligent logistics system includes: warehouse location problem, logistics network, wave planning, intelligent order allocation, order fulfilment time forecast, order combination , etc; at the same time, the team will also conduct in-depth exploration in some non-traditional business directions, such as users expect delivery time prediction, cash-on-delivery order risk control, packaging material recommendation, etc. Through the in-depth iteration of traditional business and non-traditional business, build a smart logistics system to achieve the ultimate goal of reducing costs, increasing efficiency, and improving user experience. We are looking for talented individuals to join us in 2024. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates’ jobs globally. Applications will be reviewed on a rolling basis – we encourage you to apply early. Responsibilities – Responsible for the developing of deep learning models and related intelligent systems for the supply chain and logistics of international E-Commerce business. – Participate in the process of optimizing the business results by using some of the following techniques: computer vision, natural language processing, sales prediction, time-series, geo-coding, etc.. – Keep track of cutting-edge technologies in the fields of computer vision, natural language processing and multi-modal machine learning; make use of these technologies to optimize the results in tasks such as fine-grained product style analysis, product similarity analysis and product attribute recognition, etc. – Support the production of scalable and optimised AI/machine learning (ML) models – Focus on building algorithms for the extraction, transformation and loading of large volumes of realtime, unstructured data to deploy AI/ML solutions from theoretical data science models – Run experiments to test the performance of deployed models, and identifies and resolves bugs that arise in the process – Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm – Work with the relevant software platforms in which the models are deployed Qualifications – Final year or recent graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline – Have in-depth study in a certain field of natural language processing or computer vision, including but not limited to: image/video classification and recognition, image segmentation, object detection, OCR, graph neural network, text classification, NER, multimodal, unsupervised and self-supervised learning; – Familiar with at least one framework of TensorFlow / PyTorch / MXNet and its training and deployment details, as well as the training acceleration methods such as mixed precision training and distributed training; – Familiar with the latest research and technology in model compression acceleration, including but not limited to model quantization, pruning, knowledge distillation, as well as inference frameworks such as TensorRT; – Have strong practical ability, winners in Kaggle, COCO, ImageNet, NOI/IOI and other competitions are preferred, and those who have papers published in relevant competitions and top academic conferences (such as CVPR, ICCV, ECCV, ACL, EMNLP, etc.) are preferred as well; – Familiar with AutoML related algorithms, preferably with experience in automatic search of network structure or hyper parameters; – Familiar with big data related frameworks and application, those who are familiar with MR or Spark are preferred 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. By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy. If you have any questions, please reach out to us at apac-earlycareers@tiktok.com.