About the Role

This is an early career role at Annapurna Labs (AWS) for 2026 graduates to work on cutting-edge AI silicon and systems. You'll contribute to projects like designing AI chips, building distributed systems, and optimizing compilers for ML acceleration. The role offers multiple technical tracks in hardware, software, and ML infrastructure.

Key Responsibilities

• Work on projects impacting millions of AWS customers by tackling real technical challenges in AI acceleration
• Contribute to designing next-generation AI chips and hardware architecture
• Develop and optimize distributed systems and compiler optimizations for ML training
• Participate in hardware/software integration and performance engineering
• Engage in pre/post silicon validation and ML infrastructure development

Required Skills & Qualifications

Must Have:

• Recent or upcoming graduate (within 12 months) with BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related technical field
• Experience programming in languages such as C/C++, Python, Java, or Perl
• Experience in two or more areas: hardware design (RTL, Verilog, FPGA), systems programming/low-level software, compiler design/optimization, ML frameworks (PyTorch, JAX, TensorFlow), distributed systems/parallel computing, or performance analysis/optimization

Nice to Have:

• 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

Benefits & Perks

• Base pay ranging from $99,500 to $200,000/year depending on geographic market and experience
• Equity, sign-on payments, and other forms of compensation as part of total package
• Full range of medical, financial, and/or other benefits
• Inclusive culture with workplace accommodations for disabilities