Description
Summary
Microsoft AI are looking for a talented Principal Applied Scientist at their Beijing office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising the field of AI. You'll work directly with leadership to shape the company's direction in the AI market.
About the Role
We are seeking an Applied Scientist / AI Architect with strong hands-on experience in building and optimizing large language models (LLMs), agentic AI systems, and end-to-end model training workflows. This role is ideal for scientists with a solid applied background who can translate state-of-the-art research into real-world impact. A research-oriented mindset with publications in top AI/ML venues is highly preferred but not strictly required.
Accountabilities
- Design and implement advanced LLM-based architectures and agentic systems for real-world product scenarios.
- Translate research breakthroughs into production-ready algorithms, contributing to core capabilities such as reasoning, planning, long-term memory, code-gen based design.
- Monitor and improve model performance post-deployment through data-driven iteration and error analysis.
- Collaborate across teams to deliver robust, scalable models aligned with product objectives and user value.
- Contribute to the organization’s scientific direction by identifying research opportunities that drive long-term differentiation.
The Candidate we're looking for
Experience:
- M.S. or Ph.D. in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
- 5+ years of experience in applied machine learning, with a focus on LLMs, agent systems, or reinforcement learning.
Technical skills:
- Strong hands-on experience with prompt engineering, context engineering, retrieval-augmented generation (RAG), tool use, planning agents, and long-context modeling, etc.
- Familiarity with model training pipelines using PyTorch, TensorFlow, JAX, or similar frameworks, evaluation strategies, and model deployment best practices.
Personal attributes:
- Strong coding and debugging skills, and comfort working in cross-functional, agile environments.
Benefits
- Competitive salary and benefits package.
- Opportunities for professional growth and development.
- Collaborative and dynamic work environment.
- Access to cutting-edge technology and resources.