Software Engineer, Hardware Accelerators Performance (GPUs/TPUs)

Google DeepMind; Mountain View (CA); On-site; USD 147,000 - 210,000; Full time

Benefits offered by this job

Equity

Job summary

Google DeepMind is seeking a Software Engineer to advance Gemini model training and serving on TPUs and GPUs. You will work on 2D/3D simulations, test problems in physics simulators, and build visualization and benchmarks to push performance.

You will design high‑performance kernels, profile large-scale workloads, and help shape compiler passes and hardware-aware optimizations. This role offers the chance to impact cutting‑edge AI research and practical systems at scale in Mountain View or San

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in C++ or Python.
• Experience with profiling tools (e.g., gProf, Valgrind, or VTune) for performance optimization.
• Experience in software development for hardware accelerators (e.g., CPUs, GPUs, or TPUs), including memory-hierarchy or instruction-level tuning.

Responsibilities

• Improve the training and serving efficiency of Gemini models on hardware accelerators (TPUs and GPUs), spanning model configurations, execution runtimes, and dedicated compiler passes.
• Profile large-scale distributed workloads to diagnose compute, memory, and communication bottlenecks, identifying high-impact optimization opportunities.
• Design and implement high-performance, low-level custom kernels for critical model operators to unlock peak hardware utilization.
• Build and maintain automated benchmarking pipelines and diagnostic tooling to track, reproduce, and guard against performance regressions.
• Influence next-generation accelerator architectures and compiler roadmaps by feeding back empirical workload profiles and model requirements.

Skills

C++

Python

Profiling tools

Hardware accelerators

Education

Bachelor's degree or equivalent

Master's degree or PhD

Job description

Google DeepMind is seeking a Software Engineer to advance Gemini model training and serving on TPUs and GPUs. You will work on 2D/3D simulations, test problems in physics simulators, and build visualization and benchmarks to push performance.

You will design high‑performance kernels, profile large-scale workloads, and help shape compiler passes and hardware-aware optimizations. This role offers the chance to impact cutting‑edge AI research and practical systems at scale in Mountain View or San