1 day ago
Responsibilities
- Lead customer onboarding and optimization for ML training and serving solutions on TPU platforms.
- Set technical direction and architect training and inference onboarding and optimization frameworks.
- Work directly with customers to bring ML workloads into production and optimize them.
- Collaborate with ML research, performance, model optimization tooling, and related optimization teams.
- Ship stable TPU-based training and inference optimization solutions.
- Prepare and optimize large reference models for large-scale single-host and multi-host inference.
Requirements
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 4 years of experience leading ML design and optimizing ML infrastructure, including model deployment, evaluation, data processing, debugging, or fine-tuning.
- 2 years of experience with state-of-the-art training and inference techniques, including technologies such as Megatron-LM, DeepSpeed, TensorRT-LLM, vLLM, or SGLang.
- Preferred: Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Preferred: experience optimizing ML models for large-scale training and inference workloads.
- Preferred: experience with ML optimization techniques for improving latency and throughput.
- Preferred: experience with TPUs, GPUs, or HPC.
Tech Stack
Google Cloud
Categories
About Google
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