This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
At Annapurna Labs, an Amazon company, we're not just participating in the AI revolution, we're accelerating it. We design custom silicon and revolutionary software systems that were considered impossible just yesterday, powering the world's most advanced AI infrastructure at AWS. From training the largest language models on Earth to developing breakthrough ML accelerator chips, we're inventing the future of cloud computing. We're seeking bold innovators and builders for our Fall 2026 internship program. At Annapurna Labs, you'll work on projects that directly impact millions of AWS customers worldwide, tackling real technical challenges that push the boundaries of what's possible in AI acceleration. Our program offers multiple technical tracks, matching your skills and interests with projects across our organization.
Requirements:
Work 40 hours/week minimum and commit to 12 week internship maximum
Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related technical field
Must be enrolled in a full-time degree program at time of application and returning to school after the internship
Programming experience in C, C++, Python, or similar languages
Experience in two or more of the following areas: 1. Systems programming or low-level software development 2. Compiler design or optimization 3. Machine learning frameworks (PyTorch, JAX, TensorFlow) 4. Distributed systems or parallel computing 5. Performance analysis and optimization 6. Hardware design (RTL, Verilog, FPGA development)
Nice to have:
Previous 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