Job Description
About the Role
This role builds the foundation for production-grade distributed AI training at scale. You will design reusable training recipes, benchmarking frameworks, and evaluation standards that enable large customers to train and compare models efficiently across multi-node GPU clusters. You'll work closely with platform, orchestration, and application engineers to turn distributed training best practices into repeatable, customer-facing templates.
Job Details Build and maintain production-ready distributed training recipes using frameworks such as TorchTitan and Megatron-LM Define model scaling baselines and tuning guidance across GPU counts, parallelism strategies, and checkpointing patterns Design and run multi-node communication and performance benchmarks (throughput, MFU, cost, energy efficiency) Create standardized evaluation harnesses and offline benchmarking suites for model comparison Publish training efficiency playbooks and benchmark results to guide internal tea...
This role builds the foundation for production-grade distributed AI training at scale. You will design reusable training recipes, benchmarking frameworks, and evaluation standards that enable large customers to train and compare models efficiently across multi-node GPU clusters. You'll work closely with platform, orchestration, and application engineers to turn distributed training best practices into repeatable, customer-facing templates.
Job Details Build and maintain production-ready distributed training recipes using frameworks such as TorchTitan and Megatron-LM Define model scaling baselines and tuning guidance across GPU counts, parallelism strategies, and checkpointing patterns Design and run multi-node communication and performance benchmarks (throughput, MFU, cost, energy efficiency) Create standardized evaluation harnesses and offline benchmarking suites for model comparison Publish training efficiency playbooks and benchmark results to guide internal tea...