AI Algo Eng - LLM/VLM Mandarin Required

Responsibilities

Foundation Models & Multimodal AI
- Develop production AI systems based on LLMs, VLMs, and multimodal foundation models.
- Design algorithms to understand complex signals across text, images, video, and audio.
- Build scalable multimodal intelligence for large-scale content understanding and decision-making.
- Enhance semantic understanding, classification, retrieval, and reasoning across diverse content formats.

Agentic AI
- Design and build production-grade Agent systems, including:
- ReAct
- PlanAct / CodeAct
- Tool Use & Function Calling
- Multi-Agent Architectures
- Context Engineering & Memory Management
- MCP / A2A
- Agent Orchestration
- Task Planning & Intent Understanding
- Productionise Agent systems to deliver measurable improvements to real-world products used by hundreds of millions of users.

Foundation Model Training
- Participate in the full model lifecycle, including:
- Pre-training
- Supervised Fine-Tuning (SFT)
- Reinforcement Learning (RL)
- Post-Training
- Improve model reasoning, planning, and multimodal capabilities.
- Design evaluation methodologies for models and Agent systems.
- Develop reward models and optimization pipelines for real-world production objectives.

Applied AI Research
- Evaluate emerging developments in LLMs, VLMs, Agentic AI, and multimodal learning.
- Translate frontier research into scalable production systems.
- Contribute to technical direction, architecture, and AI best practices.
- Opportunities to contribute to publications at leading AI conferences.

Requirements
- Master’s degree or above in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, or related disciplines.
- Approximately 3–5+ years of relevant industry experience.
- Strong understanding of:
- Large Language Models
- Vision Language Models
- Multimodal Foundation Models
- Agentic AI
- Hands-on experience with:
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- Agent evaluation frameworks
- Model evaluation
- Experience with modern Agent architectures, including:
- ReAct
- PlanAct
- CodeAct
- Multi-Agent Systems
- Context Engineering
- Function Calling
- MCP
- A2A
- Familiarity with:
- SFT
- RLHF / RL
- Post-Training
- Reward Models
- CodeRL or equivalent reinforcement learning infrastructure
- Strong engineering skills with the ability to translate research ideas into production AI systems.
- Professional Mandarin communication skills are required due to close collaboration with engineering and research teams based in China.

Preferred Experience
- Production experience with Vision Language Models or multimodal foundation models.
- Experience building production Agent systems at significant scale.
- Background in recommendation systems, search, content understanding, trust & safety, or content moderation.
- Experience with large-scale model training or post-training.
- Publications at conferences such as NeurIPS, ICLR, ICML, CVPR, ICCV, ACL, EMNLP, or KDD are advantageous.

Why Join
- Work at the intersection of frontier AI research and large-scale consumer products.
- Build production AI systems operating across one of the world’s largest content ecosystems.
- Engage with cutting-edge LLMs, VLMs, Agentic AI, and multimodal foundation models.
- See advances in model capability translate directly into impact for hundreds of millions of users worldwide.