Applied Scientist, AWS Neuron Science Team

Amazon • Santa Clara, CA

85d • $136,000 - $223,400

About The Position

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. We actively work on these areas: AI for Systems, Machine Learning Compiler, System Robustness, and Efficient Kernel Development.

Requirements

• PhD in computer science, computer engineering, or related field.
• Experience in patents or publications at top-tier peer-reviewed conferences or journals.
• Experience in 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.

Nice To Haves

• 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.

Responsibilities

• Develop and apply ML/RL approaches for kernel/code generation and optimization.
• Create advanced compiler techniques for ML workloads.
• Build tools for accuracy and reliability validation.
• Design high-performance kernels optimized for ML accelerator architectures.

Benefits

• Comprehensive medical, financial, and other benefits.
• Equity and sign-on payments may be provided as part of a total compensation package.
• Flexible working culture to support work-life balance.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree