Senior Applied Scientist, AWS Neuron Science team

About the role

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: 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

About the team

AWS Neuron is the software stack for Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, enabled by AWS Neuron. Neuron includes an ML compiler and native integration into popular ML frameworks. Our products are used at scale with external customers like Anthropic and Databricks, as well as internal customers like Alexa, Amazon Bedrock, Amazon Robotics, Amazon Ads, Amazon Rekognition, and many more.

Requirements

• 3+ years of experience building machine learning models for business applications
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python, or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLlib, MxNet, TensorFlow, NumPy, SciPy, etc.
• Experience with large-scale distributed systems such as Hadoop, Spark, etc.

Benefits

Amazon offers comprehensive benefits including:

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and optional supplemental life plans)
• Employee Assistance Program (EAP) and mental health support
• Medical Advice Line and Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off and parental leave
• Sign-on payments and restricted stock units (RSUs)

Learn more about our benefits at amazon.jobs/en/benefits.

Pay

USA, CA, Cupertino - $192,200.00 - $260,000.00 USD annually