Amazon
Company
Sr. Software Development Engineer, ML Infrastructure Team
US, CA, Cupertino
Job Description
Want to help drive the success of Machine Learning technologies at AWS? Do you have the skills and motivation to build automation that supports the success of peer teams? We want to talk to you!
We seek a Software Development Engineer for the Machine Learning (ML) Infrastructure team to build the tools that are used to guarantee top performance of AWS ML and High Performance Computing (HPC) technologies developed by our organization. Bring your exceptional knowledge of CI/CD automation, ML and HPC benchmarks and applications to bear on the cutting-edge software we develop. Join us as we expand the AWS offerings for AI, including Trainium, Neuron and the Elastic Fabric Adapter (EFA).
Key job responsibilities
Be an autonomous engineer on a team that builds and maintains the infrastructure that monitors and reports on functionality and performance of massive testing workloads run at scale. Use internal Amazon CI/CD tools, Linux, and public AWS products to automate the delivery of our software to customers, saving developer time. Write Python code that effortlessly spools up large clusters and runs benchmarks and applications for ML and HPC workloads. Use AWS Managed Grafana and Athena to digest the massive amount of performance data generated by these workloads and create dashboards for developers and stakeholders. Invent automatic mechanisms to alert developers to functional and performance regressions so they never reach reach customers. Manage the complexity of infrastructure that covers many instance types, software stacks, Linux operating systems, cutting-edge releases and make it easy to evolve.
A day in the life
You use Typescript and the CDK to ensure all infrastructure setup is code (IoC), reviewed and committed to automated pipelines. You find innovative ways to schedule work using SLURM and Active Directory, supporting multiple teams of developers while keeping cluster costs down. You write crisp designs for your projects, communicating clearly to your peers what you will build.
About the team
We are part of Annapurna Labs, a subsidiary in AWS that builds software and hardware that make ML on EC2 work. Our organization is a dedicated group of innovators that have invented new networks, new silicon, new software suites, and combined those to entice customers to move immense ML and HPC workloads to the cloud. The ML Infrastructure team is laser focused on making AWS the best and most cost-effective place for customers to do AI at scale.
We seek a Software Development Engineer for the Machine Learning (ML) Infrastructure team to build the tools that are used to guarantee top performance of AWS ML and High Performance Computing (HPC) technologies developed by our organization. Bring your exceptional knowledge of CI/CD automation, ML and HPC benchmarks and applications to bear on the cutting-edge software we develop. Join us as we expand the AWS offerings for AI, including Trainium, Neuron and the Elastic Fabric Adapter (EFA).
Key job responsibilities
Be an autonomous engineer on a team that builds and maintains the infrastructure that monitors and reports on functionality and performance of massive testing workloads run at scale. Use internal Amazon CI/CD tools, Linux, and public AWS products to automate the delivery of our software to customers, saving developer time. Write Python code that effortlessly spools up large clusters and runs benchmarks and applications for ML and HPC workloads. Use AWS Managed Grafana and Athena to digest the massive amount of performance data generated by these workloads and create dashboards for developers and stakeholders. Invent automatic mechanisms to alert developers to functional and performance regressions so they never reach reach customers. Manage the complexity of infrastructure that covers many instance types, software stacks, Linux operating systems, cutting-edge releases and make it easy to evolve.
A day in the life
You use Typescript and the CDK to ensure all infrastructure setup is code (IoC), reviewed and committed to automated pipelines. You find innovative ways to schedule work using SLURM and Active Directory, supporting multiple teams of developers while keeping cluster costs down. You write crisp designs for your projects, communicating clearly to your peers what you will build.
About the team
We are part of Annapurna Labs, a subsidiary in AWS that builds software and hardware that make ML on EC2 work. Our organization is a dedicated group of innovators that have invented new networks, new silicon, new software suites, and combined those to entice customers to move immense ML and HPC workloads to the cloud. The ML Infrastructure team is laser focused on making AWS the best and most cost-effective place for customers to do AI at scale.
Amazon
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