Senior Software Engineer, ML Deployment Optimization

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another

• Lead the deployment and performance optimization of critical ML models from strategic third-party developers on Google Tensor SoCs
• Design and implement full-stack (e.g., model architecture, compilers, frameworks, kernels, hardware) optimization strategies
• Architect, design, and develop reusable tools, libraries, and infrastructure to accelerate ML deployment and performance analysis
• Provide technical leadership and mentorship to junior engineers, and establish/refine best practices, processes, and guidelines for efficient ML deployment on Tensor platforms
• Collaborate with and influence external partners and internal teams to improve the ML ecosystem and provide feedback for future hardware/software designs

• Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience
• 5 years of experience with software development in C++ and Python
• Experience in technical leadership, leading project teams, and setting technical direction
• Experience in one or more of the following: machine learning deployment, ML frameworks/compilers, performance analysis, computer architecture, embedded systems development, accelerator programming

• Excellent problem-solving, debugging, communication, and mentoring skills
• Experience influencing hardware or software design based on performance insights
• Experience working directly with external partners or customers
• Experience optimizing software performance for systems on mobile or edge devices
• Knowledge of ML model architectures, ML compilers, and runtime frameworks (e.g., TensorFlow Lite)

Google's mission is to organize the world's information and make it universally accessible and useful