About the job
We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company. Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume.
Responsibilities
Design algorithms and systems that leverage LLMs and generative models for content-to-commerce matching, product summarization, etc
Explore novel architectures and strategies for generative recommendation systems
Contribute to the research community via internal papers, patents, or external publications
Drive scientific rigor while balancing real-world constraints
Qualifications
Minimum
1. Individuals who are completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
2. Strong foundation in machine learning, with knowledge of cutting-edge AI technologies; publications in accredited academic conferences or competition experience are preferred.
3. Familiarity with big data frameworks such as Hadoop, MapReduce, and Spark.
4. Experience with TensorFlow or PyTorch for model training and deployment; understanding of training acceleration techniques such as mixed precision and distributed training.
Preferred
1. Knowledge of model compression and inference acceleration techniques, including but not limited to quantization, pruning, distillation, and TensorRT optimization.
2. Expertise in at least one of the following areas:
- Computer Vision & Multimodality: In-depth research experience in multimedia or computer vision fields, including but not limited to image search, image/video classification and recognition, image segmentation, object detection, OCR, graph neural networks, multimodal learning, and unsupervised/self-supervised learning. Experience with large-scale CV/multimodal models, particularly in e-commerce scenarios, including developing and optimizing multimodal models for e-commerce videos and products. Ability to integrate LLMs with video/product representations to support tasks such as multimodal classification, video QA, cross-modal retrieval, and product categorization, with performance significantly surpassing production models. Strong hands-on experience, with achievements in competitions such as Kaggle, COCO, ImageNet, Ac