Graviton Performance Engineer – Open Source & Systems

Amazon Inc.

Cupertino (CA)

On-site

USD 193,000 - 262,000

Full time

14 days+

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Benefits offered by this job

Health insurance
401(k) matching
Paid time off
Parental leave

Job summary

Amazon Inc. in Cupertino, CA seeks a Sr Software Development Engineer to optimize performance for Graviton processors and AWS services. You will work on Linux kernel components, C++, and Rust, improving performance across open-source projects and internal systems.

You will drive analysis, design, and mentoring within a team that touches databases, web services, compilers, video encoding, ML and HPC workloads. Hardware knowledge is helpful but not required.

Qualifications

  • 5+ years of non-internship professional software development experience
  • 5+ years of programming with at least one software programming language experience
  • 5+ years of leading design or architecture of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team
  • Experience contributing to open-source projects is a plus

Responsibilities

  • Performance Analysis and Optimization: root cause and enhance software architectures, algorithms
  • Optimize software performance for AWS customers and AWS services: S3, Lambda, EMR, ElastiCache, RDS, and others
  • Open Source Development: contribute to Linux kernel improvements and other public projects
  • Develop analysis frameworks and automation systems

Skills

Performance analysis
Optimization
Linux kernel
C++
Rust
Mentor/leadership

Education

Bachelor's degree in computer science or equivalent

Job description

Amazon Inc. in Cupertino, CA seeks a Sr Software Development Engineer to optimize performance for Graviton processors and AWS services. You will work on Linux kernel components, C++, and Rust, improving performance across open-source projects and internal systems.

You will drive analysis, design, and mentoring within a team that touches databases, web services, compilers, video encoding, ML and HPC workloads. Hardware knowledge is helpful but not required.

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