Senior Staff AI/ML Infrastructure Engineer

Google LLC; Sunnyvale (CA); On-site; USD 262,000 - 364,000; Full time

Job summary

Google LLC in Sunnyvale, CA is seeking a Senior Staff Software Engineer, AI/ML for Google Cloud Compute Infrastructure. You will shape the future of AI/ML hardware acceleration, leading TPU architecture and integration within high‑scale AI systems.

This role demands hands‑on design, verification, and cross‑disciplinary leadership. You’ll drive the hardware/software co‑design roadmap, build simulation and performance tools, and mentor teams across hardware, compiler, and ML research.

Qualifications

• Bachelor's degree or equivalent in CS/EE or related field.
• 8+ years in software development, systems engineering, or related fields.
• 5+ years in ML systems, architecture, performance modeling, or simulations.
• Experience with ML frameworks (JAX, PyTorch, TensorFlow) and LLM workloads.

Responsibilities

• Lead technical goal, roadmap, and software architecture for hardware/software co-design for large-scale ML systems.
• Design and oversee simulation frameworks, performance models, and analysis tools.
• Architect scalable software, kernels, and execution pipelines linking ML models to custom silicon.
• Drive system-level optimization across distributed ML infrastructure (compute, memory, interconnects).
• Provide technical leadership across hardware, compiler, and ML research teams.

Skills

ML frameworks

LLM workloads

Hardware/software co-design

Performance modeling

Education

Bachelor’s degree in CS/EE or related

Master/PhD in Engineering/CS (preferred)

Tools

Accelerator programming

ML compilers

DL execution models

Job description

Google LLC in Sunnyvale, CA is seeking a Senior Staff Software Engineer, AI/ML for Google Cloud Compute Infrastructure. You will shape the future of AI/ML hardware acceleration, leading TPU architecture and integration within high‑scale AI systems.

This role demands hands‑on design, verification, and cross‑disciplinary leadership. You’ll drive the hardware/software co‑design roadmap, build simulation and performance tools, and mentor teams across hardware, compiler, and ML research.