About Google
Learn more about Google. Explore our innovative AI products and services, and how we. Backed by Kleiner Perkins.
About the role
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search.
What they're looking for
- Bachelor’s degree or equivalent practical experience
- 8 years of experience in software development
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning)
- Experience with modern GPU architectures, memory hierarchies, and performance bottlenecks
- Experience with low-level GPU programming (CUDA, Triton, CUTLASS, etc.) and performance engineering techniques
- Experience with modern LLMs and their deployment on AI accelerators
More about this role
- Identify and maintain LLM training and serving benchmarks; use them to identify performance opportunities, drive XLA:GPU/Triton performance and guide XLA releases.
- Partner with product teams (e.g., Google DeepMind) to onboard, optimize, and scale LLMs and machine learning models on GPU hardware.
- Conduct architecture-level simulations, performance benchmarking, and roofline analyses using tools like TRT-LLM, vLLM, and SGLang to guide system designs.
- Analyze fleet-wide performance and efficiency metrics to identify bottlenecks and engineer scalable optimizations across Google's infrastructure.
- Research and implement model/data efficiency techniques, tooling, and profiling mechanisms to improve workload performance and training efficiency.
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience with modern GPU architectures, memory hierarchies, and performance bottlenecks.
- Experience with low-level GPU programming (CUDA, Triton, CUTLASS, etc.) and performance...
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