New 
Machine Learning Engineer II
 Microsoft | |
 United States, Washington, Redmond | |
 Aug 14, 2025 | |
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OverviewThe Microsoft Copilot Studio Applied Science and Research team is looking for a Machine Learning Engineer II. The Microsoft Copilot Studio Applied Science and Research organization is seeking a Machine Learning Engineer II to contribute to the development and integration of cutting-edge AI technologies into Microsoft Copilot Studio, ensuring they are inclusive, ethical, and impactful. You will collaborate across product, design, research and engineering teams to bring innovative solutions to life, applying your expertise in machine learning, data science, and software engineering to solve complex problems. Your work will directly influence product quality and customer experiences. This role will combine machine learning and AI knowledge with software engineering expertise, while demonstrating a growth mindset and customer empathy. Join us in shaping the future of AI agents. You will play a crucial role in developing the Copilot Studio Applied Science and Research team's direction in machine learning, Generative AI model fine-tuning, Agent creation and deployment, AI evaluation and scaling. Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
ResponsibilitiesBuild and maintain internal tools to streamline model fine-tuning and evaluation workflows and automate repetitive tasks within secure development environments.Prepare and analyze data for machine learning, identifying optimal features and addressing data gaps.Implement machine learning algorithms, large-scale model fine-tuning, especially with closed and open source LLMs, SLMs, multimodal or task-specific models to solve real-world customer problems and deliver measurable product and customer impact.Contribute to or enhance existing innovations by refining models and training techniques through iterative improvements.Develop frameworks to assess model performance, monitor model behavior, conduct systematic benchmarking, and address identified weaknesses while ensuring compliance with customer standards.Write production codes and debug complex distributed systems.Provide subject matter expertise in AI subfields (e.g., deep learning, Generative AI, NLP, muti-modal models, reinforcement learning) to help translate cutting-edge research into practical, real-world solutions that drive product innovation and business impact.Demonstrate an understanding of small and large language models (SLMs and LLMs) architecture and optimization techniques to adapt out-of-the-box solutions to particular business problems. | |