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.

XML job scraping automation by YubHub

Microsoft are looking for a talented Senior Applied Scientist at their Suzhou office. This role sits at the heart of strategic decision-making, turning market data into actionable insights for a company that's revolutionising the AI and engineering system. You'll work directly with leadership to shape the company's direction in the global Office users market.

About the Role

We are seeking a highly skilled and motivated Applied Scientist with strong hands-on experience in building and optimizing agentic AI systems. Our mission is to benefit Office users with rich content and tool support to raise productivity, and we are building the AI and engineering system to make it happen. This position offers an exciting opportunity to design and develop highly complex and comprehensive systems combining engineering, AI and human participation. You will work closely with product managers, designers, and users to turn ideas and AI into reality and make a great impact to all global Office users.

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.
• Experience on office document generation and related applications is a plus.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.
• Access to cutting-edge technology and resources.
• Flexible work arrangements and work-life balance.

XML job scraping automation by YubHub

Microsoft are looking for a highly skilled and motivated Applied Scientist with strong hands-on experience in building and optimizing agentic AI systems. Our mission is to benefit Office users with rich content and tool support to raise productivity, and we are building the AI and engineering system to make it happen.

About the Role

We are seeking a highly skilled and motivated Applied Scientist with strong hands-on experience in building and optimizing agentic AI systems. Our mission is to benefit Office users with rich content and tool support to raise productivity, and we are building the AI and engineering system to make it happen. This position offers an exciting opportunity to design and develop highly complex and comprehensive systems combining engineering, AI and human participation. You will work closely with product managers, designers, and users to turn ideas and AI into reality and make a great impact to all global Office users.

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.
• Experience on office document generation and related applications is a plus.

Benefits

• Competitive salary and benefits package.
• Opportunities for professional growth and development.
• Collaborative and dynamic work environment.
• Access to cutting-edge technology and resources.
• Flexible work arrangements and work-life balance.

XML job scraping automation by YubHub