全职 LLM-MLLM Algorithm Engineer - Global E-Commerce 工作, 薪水, BYTEDANCE PTE. LTD. 公司招聘中 - Ricebowl

• Large language Model Algorithm Development: Build domain-specific large language models (LLM/MLLM) for e-commerce, integrating domain knowledge to rapidly apply models to business scenarios.
• E-commerce Governance Optimization: Understand e-commerce governance scenarios deeply to improve merchant/product/video/live-stream/IPR governance through algorithm optimization.

Develop state-of-the-art intelligent review systems capable of "knowing why to reject" decisions.

• Model Enhancement: Handle tasks like data construction, foundational model enhancement, instruction fine-tuning, chain-of-thought (CoT) , and parameter-efficient fine-tuning (PEFT) to achieve optimal model performance in the e-commerce domain.
• Problem Solving for Governance Applications: Address challenges such as long text/sequence modeling, few-shot learning, content moderation, violation detection, and policy recommendation using large models and multimodal approaches.
• Model Development and Optimization: Research and optimize e-commerce-specific NLP and multimodal large models to improve multilingual, multi-task, and multi-modal algorithm performance across various e-commerce scenarios.

Minimum Qualifications

• Strong Technical Background: Solid foundation in machine learning and familiarity with cutting-edge AI technologies.

Preference for candidates with high-quality academic publications or competition experience.

• Big Data Proficiency: Familiarity with big data frameworks and applications like MapReduce/Spark is preferred.
• Model Training Expertise: Experience with training and deploying TensorFlow/PyTorch models.
• Model Compression and Inference Optimization: Understanding of research and techniques for model compression and inference acceleration, including quantization, pruning, distillation, and TensorRT optimization.

Preferred Qualifications Expertise in One of the Following Areas:

• Computer Vision (CV) & Multimodal: In-depth knowledge in fields such as image search, classification, segmentation, detection, OCR, graph neural networks, multimodal learning, unsupervised/self-supervised learning, etc.

Experience in CV/multimodal large model projects is preferred, especially for e-commerce scenarios like video/product multimodal modeling. Strong practical abilities, with achievements in competitions such as Kaggle, COCO, ImageNet, ActivityNet, ICPC, etc. Publications in top-tier conferences (e.g., CVPR, ICCV, ECCV) are a plus.

• Natural Language Processing (NLP): Expertise in areas such as pretraining, NLU, multilingual and cross-lingual learning, NLG, transfer learning, and semi-supervised learning.

Experience in LLM-related projects and applying them to unify e-commerce NLP tasks is a plus. Strong practical abilities, with achievements in competitions like Kaggle, GLUE, Super GLUE, CLUE, etc. Publications in top-tier conferences (e.g., ACL, EMNLP) are a plus.

• Knowledge of training acceleration methods such as mixed precision training and distributed training is a plus.