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.
About the jobAs a part of the technical Senior AI/ML Software Engineer, you will lead the architecture and deployment of large-scale distributed data systems and advanced machine learning pipelines. In this role, you will design infrastructure capable of analyzing high-throughput data streams. You will bridge the gap between High-Performance Computing (HPC) and modern AI applications, optimizing complex inference workloads for specialized hardware accelerators while guiding cross-functional engineering teams.
Google Public Sector brings the magic of Google to the mission of government and education with solutions purpose-built for enterprises. We focus on helping United States public sector institutions accelerate their digital transformations, and we continue to make significant investments and grow our team to meet the complex needs of local, state and federal government and educational institutions.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - 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.
