1 day ago
Singapore, SingaporeStaff+
Responsibilities
- Lead customer onboarding for stable ML training and serving stacks and optimize workloads on the latest TPU platforms.
- Set technical direction and architect training, inference, onboarding, and optimization frameworks.
- Work directly with customers to onboard workloads into production and improve their performance.
- Collaborate with ML research, ML performance, model optimization tooling, and other optimization teams.
- Ship stable TPU-based training and inference optimization solutions to customers.
- Prepare and optimize very large reference models and demonstrate state-of-the-art single-host and multi-host inference solutions at large scale.
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, model evaluation, data processing, debugging, or fine-tuning.
- 2 years of experience with state-of-the-art training techniques such as Megatron-LM and DeepSpeed and inference techniques such as TensorRT-LLM, vLLM, and SGLang.
- Preferred: Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Preferred: experience optimizing machine learning models for large-scale training and inference workloads.
- Preferred: experience with large-scale ML optimization techniques for improving latency and throughput.
- Preferred: experience with accelerators such as TPUs or GPUs, or with HPC.
Tech Stack
Google Cloud
Categories
About Google
Google builds consumer and enterprise software and services including Search, Android, YouTube, Chrome, Maps, Gmail, and Google Cloud. Its business model centers on digital advertising and paid cloud, software, and hardware offerings (e.g., Pixel and Nest) for consumers, developers, and organizations. Founded in 1998 and headquartered in Mountain View, California, Google operates globally as a subsidiary of Alphabet Inc.