Machine Learning Engineer Graduate (E-Commerce Supply Chain & Logistics - LLM/Agent) - 2027 Start (PhD)
Core
Building AI-native capabilities for global logistics, including logistics agents, address intelligence, and workflow automation for complex supply chain operations.
Role type
PhD-level Machine Learning Engineer (LLM/Agent Systems)
Builds
Production LLMs, agent systems, and intelligent systems for e-commerce supply chain and logistics
Domain
E-commerce, Global Supply Chain, Logistics, AI/ML
Deliverable
production ML models
Required skills
LLMs, agents, RAG, tool use, post-training, evaluation, Python, Java/C++/Go/TypeScript, PyTorch/TensorFlow/JAX, vLLM, Hugging Face, LangChain, LlamaIndex
Preferred skills
coding agents, long-horizon agents, computer-use agents, workflow orchestration, automated evaluation frameworks, LLM post-training (SFT, DPO, PPO, GRPO, RLHF), benchmarking, logistics operations research, knowledge graphs
Technologies
PyTorch, TensorFlow, JAX, vLLM, Hugging Face, LangChain, LlamaIndex, Harness
Responsibilities
Develop large language models, agent systems, and related intelligent systems for supply chain and logistics; Build and land domain LLM model capabilities covering continued pre-training, SFT, preference optimization, reinforcement learning, and business applications; Develop multimodal and structured understanding capabilities for logistics scenarios; Build core agent capabilities for team and business workflows including task decomposition, RAG, and skill/tool use; Design and improve agent architecture and engineering systems including runtime orchestration, memory management, and observability
Seniority
PhD, Research/Engineering IC