2026 Annapurna Labs at Aws, Early Career (us) - Machine Learning Systems & Silicon Innovation

Amazon Amazon · Big Tech · Cupertino, CA · Software Development

This role focuses on building and optimizing the systems and silicon that power AI infrastructure, including custom ML accelerator chips, distributed training systems, and compiler optimizations for ML training. It's an early career role within Annapurna Labs at AWS, aiming to accelerate AI development.

What you'd actually do

  1. architect next-generation AI chips that process billions of parameters?
  2. Build distributed systems that scale across thousands of accelerators?
  3. Create compiler optimizations that make ML training blazingly fast?
  4. Whether your passion lies in hardware design, distributed systems, compiler development, or ML infrastructure, we'll help you find your perfect fit and make meaningful contributions from day one.

Skills

Required

  • C/C++
  • Python
  • Java
  • Perl
  • Hardware design (RTL, System Verilog, FPGA development)
  • Systems programming or low-level software development
  • Compiler design or optimization
  • Machine learning frameworks (PyTorch, JAX, TensorFlow)
  • Distributed systems or parallel computing
  • Performance analysis and optimization

Nice to have

  • hardware/software co-design
  • ML systems
  • computer architecture
  • open-source projects
  • research publications
  • machine learning
  • parallel computing
  • computer architecture
  • compiler construction

What the JD emphasized

  • custom silicon
  • revolutionary software systems
  • AI infrastructure
  • ML accelerator chips
  • AI acceleration
  • ML Systems & Compilers
  • Systems Software & Infrastructure
  • Silicon Innovation & Design
  • Hardware design
  • Systems programming
  • Compiler design
  • Machine learning frameworks
  • Distributed systems
  • Performance analysis and optimization

Other signals

  • design custom silicon
  • revolutionary software systems
  • AI infrastructure
  • ML accelerator chips
  • architect next-generation AI chips
  • distributed systems that scale
  • compiler optimizations
  • ML training
  • hardware design
  • distributed systems
  • compiler development
  • ML infrastructure