Annapurna Labs
Technology
SoftwareDevelopmentEngineer,MLInfrastructureTeam
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Software Development Engineer, ML Infrastructure Team at Annapurna Labs. Skills: ML Infrastructure, CI/CD, Python. Build and maintain infrastructure. Monitor functionality and performance”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
3+ years software development experience, 2+ years system design experience, Experience with CI/CD pipelines, Proficiency with Linux, Experience coding in Python, Experience coding in Typescript, Experience coding in CDK
Nice to Have
3+ years full SDLC experience, Bachelor's degree in computer science
What You'll Do.
Build and maintain infrastructure
Monitor functionality and performance
Automate software delivery
Run benchmarks and applications
Invent automatic alerting mechanisms
Manage infrastructure complexity
Ensure infrastructure setup is code
Schedule work using SLURM
How You'll Work.
Team & Collaboration
Support peer teams; Support multiple developer teams
Communication Scope
Communicate designs clearly
Full 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
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