Applied Scientist – ML Systems & Accelerators

Amazon Inc.; Cupertino (CA); Hybrid; USD 172,000 - 222,000; Full time

Benefits offered by this job

Health insurance

RSUs

Sign-on payments

401(k) matching

Paid time off

Parental leave

Job summary

Amazon’s AWS Neuron Science team is seeking an Applied Scientist to advance the software stack for Trainium and Inferentia. You will partner with internal engineers and external customers to identify adoption barriers and opportunities to optimize ML workloads on our accelerators.

You will collaborate with researchers and engineers to push state-of-the-art ML systems, publish findings, and contribute to scalable, reliable software that powers real-world AI workloads across AWS customers.

Qualifications

• PhD or Master’s degree with 4+ years of CS, CE, ML or related field experience.
• Publications or patents at top-tier peer-reviewed conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.
• Experience building machine learning models or developing algorithms for business application.
• Experience in professional software development.

Responsibilities

• Identify adoption barriers and optimization opportunities for Trainium and Inferentia.
• Collaborate with engineering teams to implement ML system improvements.
• Engage with academic and research communities to advance state-of-the-art ML systems.
• Work with customers to understand needs and provide scalable solutions.

Skills

PhD or Master’s + 4+ yrs in CS/CE/ML

Publications or patents

Java

C++

Python

Algorithms & data structures

ML models / business algorithms

Professional software development

Education

PhD or Master’s degree

Job description

Amazon’s AWS Neuron Science team is seeking an Applied Scientist to advance the software stack for Trainium and Inferentia. You will partner with internal engineers and external customers to identify adoption barriers and opportunities to optimize ML workloads on our accelerators.

You will collaborate with researchers and engineers to push state-of-the-art ML systems, publish findings, and contribute to scalable, reliable software that powers real-world AI workloads across AWS customers.