LLM & Agent Algorithm Intern (Search) - 2027 Start (PhD)
Core
Building the search-domain LLM foundation and Agent execution framework to enable proactive task completion and multimodal search experiences.
Role type
PhD Research Intern (LLM & Agent Algorithms)
Builds
Search LLMs, multi-agent orchestration systems, long-term memory mechanisms, and automated evaluation frameworks.
Domain
Search, Large Language Models, Multi-Agent Systems, Multimodal AI
Deliverable
production ML models
Required skills
Machine learning, deep learning, LLM pre-training/fine-tuning/alignment, multi-agent orchestration, RAG, RLHF/RLAIF, data synthesis, automated evaluation, PyTorch, distributed training, model compression/inference acceleration
Preferred skills
Top-tier conference publications (NeurIPS/ICML/ACL/CVPR), CV/multimodal projects, NLP transfer learning, Kaggle awards
Technologies
PyTorch, TensorFlow, MapReduce, Spark, TensorRT, Quantization, Pruning, Distillation
Responsibilities
Develop post-training pipelines for search LLMs; build multi-agent cluster scheduling and collaboration algorithms; work on long-term memory and self-improvement loops; construct online Reward/Verifier systems; implement long-horizon task Agents and multimodal AIGC features.
Seniority
PhD Intern
