Staff Software Engineer, AI/ML, Google Public Sector

Job description

Architect and operate advanced data synthesis pipelines and AI-based retrieval applications. Manage petabyte-scale data ingestion and synchronization across compute environments, including local storage, cloud backends, and on-prem resources. Optimize highly parallel numerical operations and ML inference algorithms for specialized hardware accelerators. Lead technical direction and provide engineering mentorship for groups developing complex production software systems. Implement rigorous data life-cycle policies to ensure system resilience, data integrity, and fault recovery at scale. Minimum Qualifications: Bachelor's degree or equivalent practical experience. 8 years of experience programming in C++, Java, Python, Kotlin or Go. Experience in technical leadership, including defining technical road maps, delivering projects, and maintaining code quality standards. Experience in parallel computing paradigms, hardware-level optimization, and low-level accelerator optimization. Preferred Qualifications: Master's degree or PhD in a quantitative discipline (e.g., Computer Science, Physics, Applied Mathematics, or similar). 8 years of experience designing, building, and operating large-scale distributed data systems and production machine learning deployments. Experience deploying modern deep learning architectures using frameworks like PyTorch or TensorFlow on large-scale clusters. Experience with cloud-native infrastructure (Docker, Kubernetes) and managing distributed filesystems and cloud object storage. Active, or the ability to obtain, a Secret security clearance.