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Amazon Development Center U.S., Inc.
Software Development Manager, AWS Neuron SDK Distributed Training job at Cupertino, CA, United States of America
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What they do
A Software Development or Engineering Manager leads teams of software developers who design or improve computer software. Manages and oversees the software development process and directs the work of software engineers. May be primary contact with customers or users; may manage software development project budgets and hire or train staff.
$190,032 / year median in California
Job Description
AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine learning accelerators and the Trainium-based Servers that use them. As the SDM of Software Development for the Neuron Training team, you will be responsible for leading a strong team of engineers and managers to help design and deploy these new products. A successful candidate will have an established background in developing Machine Learning products with direct customer-facing experience, a strong technical ability and a motivation to achieve results. Experience in Machine Learning and software development is also a must. Responsible for the full development life cycle of our integrations and extensions for training support in Pytorch, JAX, and distributed training libraries with a focus on performance of latest ML models at scale on Trainium using latest techniques in performance optimization, accuracy, and resilience. you will lead the way to ensure support for key ML functionality in a combined chip/software platform, which will ensure the right thing is being built and delivered to customers Key job responsibilities
- Lead a team of engineers focused on enabling new ML training customers on the Neuron SDK/Trainium platform.
- Own the customer onboarding journey from model evaluation through production training at scale
- Drive engineering initiatives to maximize Model FLOPS Utilization (MFU) for customer workloads through performance analysis, profiling, and tuning tools.
- Build and maintain tooling, automation, and documentation that accelerates time-to-first-training for new customer models.
- Partner with compiler, runtime, and framework teams to identify and resolve blockers in customer workloads.
- Develop scalable processes for distributed training enablement (FSDP, DeepSpeed, Megatron, custom parallelism strategies).
- Drive technical strategy for supporting frontier model architectures (LLMs, MoE, multi-modal) on Trainium.
- Build strong cross-functional partnerships with product management, developer relations, and customer-facing teams.
- Recruit, mentor, and grow a high-performing team of ML systems engineers.