Staff Software Engineer, AI/ML, Google Public Sector

• 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.

• 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.