Description
- Experience with at least one modern language such as Java, Python, C++, or C# including object-oriented design
- Currently enrolled in a Bachelor’s degree program or higher majoring in Computer Science, Computer Engineering, Electrical Engineering or related technical field with anticipated graduation date on or later than May 2026
- Candidates with strong interests and academic qualifications/research focus in two of the following: 1. Knowledge of code generation, compute graph optimization, resource scheduling, 2. Data structure and algorithms, 3. Compiler - Optimizing compilers (internals of LLVM, clang, etc), 4. Machine Learning - Experience with XLA, TVM, MLIR, LLVM, 5. Machine Learning frameworks (PyTorch, JAX) and Machine Learning models
- Available for 12-month internship starting May 2025
- Previous technical internship(s)
- Knowledge code generation, compute graph optimization, resource scheduling
- Experience in optimization mathematics such as linear programming and nonlinear optimization
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
At AWS our vision is to make deep learning pervasive for everyday developers and to democratize access to cutting edge infrastructure. In order to deliver on that vision, we’ve created innovative software and hardware solutions that make it possible.
AWS Neuron is the SDK that optimizes the performance of complex neural net models executed on AWS Inferentia and Trainium, our custom chips designed to accelerate deep-learning workloads.
The Neuron SDK consists of a compiler, run-time, and debugger, integrated with Tensorflow, PyTorch, and MXNet. It is preinstalled in AWS Deep Learning AMIs and Deep Learning Containers for customers to quickly get started with running high performance and cost-effective inference and training.
The Neuron team is looking for students interested in learning about and contributing to deep learning compilers to solve our customers toughest problems. As a compiler engineer on the Neuron team, you will be supporting the development of a compiler targeting AWS Inferentia and Trainium - our custom Silicon ML accelerators. This is an opportunity to work on a cutting-edge product where you will implement business-critical features, and be mentored by a brilliant team of experienced engineers.
- Currently enrolled in a Bachelor’s degree program or higher majoring in Computer Science, Computer Engineering, Electrical Engineering or related technical field with anticipated graduation date on or later than May 2026
- Candidates with strong interests and academic qualifications/research focus in two of the following: 1. Knowledge of code generation, compute graph optimization, resource scheduling, 2. Data structure and algorithms, 3. Compiler - Optimizing compilers (internals of LLVM, clang, etc), 4. Machine Learning - Experience with XLA, TVM, MLIR, LLVM, 5. Machine Learning frameworks (PyTorch, JAX) and Machine Learning models
- Available for 12-month internship starting May 2025
- Previous technical internship(s)
- Knowledge code generation, compute graph optimization, resource scheduling
- Experience in optimization mathematics such as linear programming and nonlinear optimization
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
At AWS our vision is to make deep learning pervasive for everyday developers and to democratize access to cutting edge infrastructure. In order to deliver on that vision, we’ve created innovative software and hardware solutions that make it possible.
AWS Neuron is the SDK that optimizes the performance of complex neural net models executed on AWS Inferentia and Trainium, our custom chips designed to accelerate deep-learning workloads.
The Neuron SDK consists of a compiler, run-time, and debugger, integrated with Tensorflow, PyTorch, and MXNet. It is preinstalled in AWS Deep Learning AMIs and Deep Learning Containers for customers to quickly get started with running high performance and cost-effective inference and training.
The Neuron team is looking for students interested in learning about and contributing to deep learning compilers to solve our customers toughest problems. As a compiler engineer on the Neuron team, you will be supporting the development of a compiler targeting AWS Inferentia and Trainium - our custom Silicon ML accelerators. This is an opportunity to work on a cutting-edge product where you will implement business-critical features, and be mentored by a brilliant team of experienced engineers.
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