Senior AI/ML Software Engineer — HPC & Large-Scale Systems

Google; United States; On-site; USD 207,000 - 301,000; Full time

Job summary

Google Public Sector is seeking a Staff Software Engineer, AI/ML, to lead advanced AI/ML initiatives in Reston, VA. You will architect large-scale distributed data systems, optimize ML inference on specialized accelerators, and guide cross-functional teams across the product lifecycle.

This role requires deep expertise in software engineering, 8 years of experience, and strong leadership. Familiarity with Docker/Kubernetes and cloud storage is essential; security-clearance eligibility is a plus.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience programming in C++, Java, Python, Kotlin, or Go.
• Experience in technical leadership, roadmaps, and delivering projects.
• Experience in parallel computing, hardware-level optimization, and accelerator optimization.
• Master's or PhD in CS/Physics/Math preferred.
• 8 years building large-scale distributed data systems and ML deployments.
• Experience deploying DL architectures with PyTorch or TensorFlow on large clusters.
• Experience with Docker, Kubernetes, and distributed storage.

Responsibilities

• Architect and operate data synthesis pipelines and AI-based retrieval apps.
• Manage petabyte-scale data ingestion across compute environments.
• Optimize ML inference for accelerators.
• Lead technical direction and mentor engineering teams.
• Implement data lifecycle policies for resilience and integrity.

Skills

C++/Java/Python

Kotlin/Go

Technical leadership

Parallel computing

Low-level optimization

HPC

Education

Bachelor's degree or equivalent

Tools

Docker

Kubernetes

Distributed filesystems

Job description

Google Public Sector is seeking a Staff Software Engineer, AI/ML, to lead advanced AI/ML initiatives in Reston, VA. You will architect large-scale distributed data systems, optimize ML inference on specialized accelerators, and guide cross-functional teams across the product lifecycle.

This role requires deep expertise in software engineering, 8 years of experience, and strong leadership. Familiarity with Docker/Kubernetes and cloud storage is essential; security-clearance eligibility is a plus.