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

Position Overview

Annapurna Labs, an Amazon company, designs custom silicon and revolutionary software systems powering the world's most advanced AI infrastructure at AWS. We're seeking bold innovators for 2026 Early Career roles where you'll work on projects directly impacting millions of AWS customers worldwide, tackling real technical challenges that push the boundaries of what's possible in AI acceleration. The program offers multiple technical tracks, matching your skills and interests with projects across hardware design, distributed systems, compiler development, and ML infrastructure.

Responsibilities

• Work on projects that directly impact millions of AWS customers worldwide
• Tackle real technical challenges that push the boundaries of what's possible in AI acceleration
• Technical tracks include:
  • ML Systems & Compilers: Framework Optimization (PyTorch, JAX), Compiler Development & Optimization, Distributed Training Systems, Performance Engineering, ML Infrastructure Development
  • Systems Software & Infrastructure: Firmware & Driver Development, Runtime Systems, Fleet Management & Automation, Hardware/Software Integration, Performance Analysis Tools
  • Silicon Innovation & Design: RTL Development for ML Accelerators, Hardware Architecture & Modeling, Physical Design & Power Optimization, Custom Circuit Design, Pre/Post Silicon Validation

Requirements & Skills

Basic Qualifications:

• Experience programming languages such as C/C++, Python, Java or Perl
• BS, MS, or PhD in Computer Science, Computer Engineering, Applied Science, Electrical Engineering, Mechanical Engineering or related technical field
• Experience in two or more of the following areas: 1. Hardware design (RTL, System Verilog, FPGA development) 2. Systems programming or low-level software development 3. Compiler design or optimization 4. Machine learning frameworks (PyTorch, JAX, TensorFlow) 5. Distributed systems or parallel computing 6. Performance analysis and optimization

Preferred Qualifications:

• Previous industry, internship, research, or project experience in hardware/software co-design, ML systems, or computer architecture
• Contributions to open-source projects or research publications
• Completed or currently enrolled in coursework covering machine learning, parallel computing, computer architecture and/or compiler construction