Principal Software Engineer- Compute Graph Compiler (CGC) Team

A successful candidate for this position will be one who: Define and drive the technical vision, architecture, and roadmap for key components of the Windows ML compiler stack. Lead cross-team initiatives that improve AI workload performance, scalability, and efficiency across CPU, GPU, and NPU hardware. Drive NPU enablement strategy and advanced optimization techniques for next-generation AI processors. Partner with hardware vendors and internal platform teams to influence future AI hardware and software capabilities. Design and develop high-performance compiler infrastructure, execution engines, and developer tooling. Identify and solve complex systems challenges involving scheduling, memory management, code generation, graph optimization, and hardware abstraction. Mentor and support engineers across experience levels and provide technical leadership across multiple projects and organizations. Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python These requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 6+ years of experience working at low levels of software stack, device driver development, and/or integration of hardware and software Deep knowledge with hands-on experience in ML compiler, tool, and platform technology. 10+ years of experience delivering world-class system software. In-depth experience and knowledge in operating system development in either user-mode or kernel-mode driver development. A proven track record of significant technical leadership in research and development of AI platforms or frameworks technology. Prior experience in the design and development of ML hardware microarchitecture in real-world products. Proficient communication/customer interfacing skills and the ability to deal with ambiguity and prioritize issues.