Software Engineer, Hardware Accelerators Performance, GeminiApp, DeepMind

Job description

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.