SDE II: Infra for ML Workloads & Cloud Services
Amazon
Get more replies from employers
Send a job-specific resume in minutes.
Benefits offered by this job
Job summary
Amazon is seeking a Software Engineer to lead the development of services that optimize, analyze, and release ML workloads and artifacts on AWS Inferentia/Trainium accelerators. You will work with EC2, EKS, Lambda-like services and contribute from architecture to delivery, with emphasis on performance and scalability.
The role requires strong experience in distributed systems, ML projects, and security practices in DevOps, in a startup-like environment.
Qualifications
- 3+ years of non-internship professional software development experience.
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems.
- Experience with at least one software programming language.
- Knowledge of system performance, memory management, and parallel computing principles.
- Experience debugging, profiling, and implementing best practices in large-scale systems.
- Experience with AWS or cloud technologies.
Responsibilities
- Lead design and implementation of new tools, pipelines and automation across teams.
- Design, implement, and maintain CI/CD pipelines to automate the software release process.
- Collaborate with development teams to integrate new software releases.
- Infrastructure management: automate provisioning and ensure high availability and scalability.
- Implement monitoring to track performance and optimize systems.
Skills
Education
Tools
Job description
Amazon is seeking a Software Engineer to lead the development of services that optimize, analyze, and release ML workloads and artifacts on AWS Inferentia/Trainium accelerators. You will work with EC2, EKS, Lambda-like services and contribute from architecture to delivery, with emphasis on performance and scalability.
The role requires strong experience in distributed systems, ML projects, and security practices in DevOps, in a startup-like environment.
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
