About the job
The AWS Neuron Science Team is looking for talented scientists to enhance our software stack, accelerating customer adoption of Trainium and Inferentia accelerators. In this role, you will work directly with external and internal customers to identify key adoption barriers and optimization opportunities. You'll collaborate closely with our engineering teams to implement innovative solutions and engage with academic and research communities to advance state-of-the-art ML systems. As part of a strategic growth area for AWS, you'll work alongside distinguished engineers and scientists in an exciting and impactful environment.
Responsibilities
AI for Systems: Developing and applying ML/RL approaches for kernel/code generation and optimization
Machine Learning Compiler: Creating advanced compiler techniques for ML workloads
System Robustness: Building tools for accuracy and reliability validation
Efficient Kernel Development: Designing high-performance kernels optimized for our ML accelerator architectures
Qualifications
Minimum
PhD in computer science, computer engineering, or related field
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Experience programming in Java, C++, Python or related language
Experience using Unix/Linux
Preferred
Experience in investigating, designing, prototyping, and delivering new and innovative system solutions
Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
Experience with popular deep learning frameworks such as MxNet and Tensor Flow