Software Engineer, Hardware Accelerators Performance, GeminiApp, DeepMind

• 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.

Minimum 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.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
• 3 years of experience with advanced data structures, algorithms, and machine learning optimization.
• Experience developing accessible technologies.

• 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.