Amazon
Software Development Engineer I, Annapurna Labs, Early Career - 2027
$129K–$148K
Austin, TX +3 · Entry level · Full-time · Posted Sep 24, 2026
- Location
- Austin, TX
Seattle, WA
New York, NY
Cupertino, CA - Education
- Bachelor's or Master's degree program in Computer Science, Computer Engineering, or a related field; final graduation date of May 2027 or later.
About the job
Build and optimize production software across the stack that enables Amazon’s custom silicon products, including processors and machine-learning accelerators.
What you'll do
- Design, implement, test, and document software such as systems code, compilers, runtimes, and tooling.
- Optimize software performance on custom hardware and debug issues across the hardware-software boundary.
- Collaborate with hardware, compiler, and systems teams to deliver features end-to-end.
What they ask for
- Bachelor's or Master's degree program in Computer Science, Computer Engineering, or a related field, with a final graduation date of May 2027 or later.
- Programming experience in at least one modern language such as C, C++, Java, or Python.
- Coursework or project experience in data structures, algorithms, and software design.
- Understanding of core computer science fundamentals: operating systems, computer architecture, or systems programming.
Nice to have
- Degree focus in systems, compilers, computer architecture, or high-performance computing; or experience with low-level or systems programming in C/C++.
- Familiarity with compilers, ML runtimes, operating systems internals, or distributed systems; exposure to ML frameworks; or relevant internship, research, or open-source experience.
Pay
128,700.00 USD annually (base salary); 148,100.00 USD annually (base salary); 141,600.00 USD annually (base salary); 128,700.00 USD annually (base salary)
Tools
C, C++, Python, Java, Neuron SDK, MLIR, LLVM, PyTorch
AI focus
Develop software for machine-learning accelerators, runtimes, frameworks, and training and inference infrastructure; optimize software and kernels for custom silicon.
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