西门子西门子中国研究院 大模型AI Agent研究员（北京、苏州）
任职要求
• Master’s degree or above majoring in Artificial Intelligence, Computer Science, Automation, Mathematics or related. • Self-motivated, open-minded, good communication skills and good teamwork. The skills you are expected to have: • Familiar & comfortable when coding in Python & programming on Linux. • Familiar with commonly used deep learning and agent frameworks, e.g., Pytorch, TensorFlow, LangChain, LangGraph, etc. • Practical experience (in-career or academic) on LLMs – open-source model deployment, setting up RAG system, building agents with MCP, etc. • Prefer: Solid understanding about the background & theories of LLMs, agentic workflow, knowledge graph, parallel computing, etc. • Prefer:…
工作职责
We empower our people to stay curious and innovative in a fast-evolving world. We’re looking for individuals who are eager to push boundaries, learn continuously, and create meaningful impact both now and in the future. Does that sound like you? Then we’d love to have you join our dynamic and diverse global team. DAI AIX – AI Acceleration and Exploration, is at the forefront of Data Analytics and AI research within Siemens’ global technology network, driving innovation, collaboration, and transformative applications for our customers. As part of our team, you’ll engage in cutting-edge applied research and development.We are currently seeking an NLP/LLM/Agent Engineer/Researcher to work on the development and deployment of next-generation language-related applications and intelligent agents. The focus of this role is advancing the capabilities of large language models (LLMs) and their integration into real-world applications such as autonomous agents and industrial workflows. You will design and implement advanced algorithms, optimize LLM architectures for specific use cases, and develop scalable solutions that drive tangible outcomes in industry. You'll make an impact by • Research on state-of-the-art data analytics & AI technologies on a general range. • Mainly focus on modern foundation model applications in industrial scenarios1. Context engineering for foundation models2. Development of agent systems for industrial applications3. Task-specific model finetuning • Partially work with multi-modal applications • Participating in both internal & external research projects • Assist deployment of customer development/deployment project
We empower our people to stay resilient and relevant in a constantly changing world. We're looking for people who are always searching for creative ways to grow and learn. People who want to make a real impact, now and in the future. Does that sound like you? Then it seems like you'd make a great addition to our vibrant international team. DAI AIX – AI Acceleration and Exploration, is working on the cutting-edge research of Data Analytics and AI with Siemens global technology network, and consulting, co-creation, data driven applications for the end customers. Research Scientist is to do applied research for Industrial AI applications in the team. We are seeking a Reinforcement Learning (RL) Specialist to lead the design, implementation, and optimization of RL-driven systems for post-training of foundation models. The primary focus of this role is advancing our RL capabilities for real-world applications such as industrial control systems and LLM agents. You will develop cutting-edge algorithms, improve post-training efficiency, and deploy scalable RL solutions in industry. You'll make an impact by • 1. Reinforcement learning development for post-training: • Design and implement state-of-the-art RL algorithms (e.g., PPO, SAC, DQN) for post-training of foundation models like LLMs and time series foundation models. • Implement distributed RL training pipelines using frameworks like Ray RLlib, Deepspeed, or custom solutions. • Design and implement benchmark pipelines for model evaluation. • 2. Align foundation models like LLMs and time series foundation models with specific areas/tasks through techniques like SFT, RL. • 3. Coding & Infrastructure: • Write production-grade Python code using PyTorch, numpy, and pandas. • Manage Linux-based clusters for distributed training and deployment. • 4. All other support required by the line manager if necessary.