Applied Scientist, AWS Neuron Science team

Amazon Inc.; Cupertino (CA); Hybrid; USD 171,600 - 222,200; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon's AWS Neuron Science team in Cupertino is seeking an Applied Scientist to enhance the software stack for Trainium and Inferentia. This position involves collaborating with engineering teams and engaging with research communities to drive customer adoption.

The ideal candidate holds a PhD or a Master’s with relevant experience, proficient in programming languages like Java, C++, and Python, and is knowledgeable in algorithms and high-performance computing.

The role offers a competitive salary range of $171,600 – $222,200 annually, with additional benefits including health insurance and parental leave.

Qualifications

• PhD or Master’s degree in CS, CE, ML, or a related field.
• Experience with patents or publications at top-tier conferences or journals.
• Experience in algorithms, data mining, and high-performance computing.

Responsibilities

• Enhance software stack for customer adoption of Trainium and Inferentia.
• Collaborate with engineering teams on innovative solutions.
• Engage with academic and research communities in ML.

Skills

Proficiency in Java

Proficiency in C++

Proficiency in Python

Algorithms and data structures

Numerical optimization

Parallel and distributed computing

High-performance computing

Education

PhD in CS, CE, ML, or related field

Master’s degree with 4+ years experience

Job description

Applied Scientist, AWS Neuron Science team

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.

Areas of Focus

• 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, while Trainium delivers best-in-class ML training performance at the lowest training cost. Neuron provides an ML compiler and native integration into popular ML frameworks. Our products are used at scale by external customers such as Anthropic and Databricks, and internal customers including Alexa, Amazon Bedrock, Amazon Robotics, Amazon Ads, and Amazon Rekognition.

Basic Qualifications

• PhD, or Master’s degree with 4+ years of experience in CS, CE, ML, or a related field.
• Experience with patents or publications at top-tier peer‑reviewed conferences or journals.
• Proficiency in Java, C++, Python, or a related programming language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, or high‑performance computing.

Preferred Qualifications

• Experience building machine learning models or developing algorithms for business applications.
• Experience in professional software development.

Equal Opportunity

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Location and Compensation

USA, CA, Cupertino – salary range: 171,600.00 – 222,200.00 USD annually. The Amazon package includes sign‑on payments, restricted stock units (RSUs), and additional benefits such as health insurance, 401(k) matching, paid time off, and parental leave.

Posted

Posted: January 30, 2026