Provide coaching, mentorship, and career growth for engineers working across large-scale distributed ML systems, performance optimization, and open-source generative AI models. Partner with Tech Leads, product management, and cross-functional teams to define and execute the roadmap for scalable JAX-based LLM (MaxText) and Diffusion (MaxDiffusion) frameworks. Guide the team in implementing core performance optimizations (e.g., quantization, sparsity, custom kernels) and supporting new accelerator architectures (TPUs and GPUs) on GCP AI Hypercomputer.
Collaborate closely with DeepMind, Core ML, and the open-source community to deliver high-quality, reusable software artifacts and benchmark-setting MLPerf submissions. Balance rapid model innovation with sustainable engineering practices, operational reliability, and high-trust team environment.
Job description provided by Google.
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