Applied Scientist 2

The Copilot Asia ML Team is driving the next generation of intelligent assistant infrastructure, powering Microsoft Copilot experiences across the enterprise. Our mission is to build foundational language models that make Copilot more helpful, responsive, and accessible to millions of users worldwide.

• Design and implement efficient workflows for training, distillation, and fine-tuning Small and Large Language Models (SLMs), leveraging techniques such as LoRA, QLoRA, and instruction tuning.
• Apply model compression strategies—including quantization (e.g., GPTQ, AWQ) and pruning—to reduce inference costs and improve latency.
• Optimize LLM inference performance using frameworks like vLLM and TensorRT-LLM (TRT-LLM) to enable scalable, low-latency deployment.
• Build robust and scalable inference systems tailored to heterogeneous production environments, with a strong focus on performance, cost-efficiency, and stability.
• Develop evaluation datasets and metrics to assess model performance in real-world product scenarios.
• Build and maintain end-to-end machine learning pipelines encompassing data preprocessing, training, validation, and deployment.
• Collaborate closely with product managers, engineers, and research scientists to translate business needs into impactful AI solutions, driving real-world adoption and seamless product integration.

• Master’s degree or above (or equivalent experience) in Computer Science, Engineering, Mathematics, Physics, or a related field.
• Strong programming skills with hands-on experience in managing large-scale data and machine learning pipelines.
• Deep understanding of open-source ML frameworks such as PyTorch, vLLM, and TensorRT-LLM (TRT-LLM).
• Solid knowledge of model optimization techniques, including quantization, pruning, and efficient inference.

• 401k matching
• Health insurance
• Flight privileges
• Generous time away
• Giving programs
• Discounts on products and services
• Savings and investments
• Maternity and paternity leave

Microsoft is committed to provide Employees with equal opportunity for learning and personal growth.