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Posted via Amazon Jobs

Senior Software Engineer - AI/ML, AWS Neuron Inference

Posted Aug 3, 2026

Role at a glance

Salary
$168.1K – $227.4K/yr
Location
Seattle, Washington, United States
Work arrangement
On-site
Employment
Full-time
Experience
5+ years of full software development life cycle
Education
Bachelor's degree in computer science or equivalent

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Role Summary

AI-generated

The Machine Learning Inference Applications team develops and optimizes core building blocks for large language model inference on AWS Neuron, the software stack for Inferentia and Trainium accelerators. The role works with chip architects, compiler engineers, and runtime engineers to improve performance and accuracy across open-source and internally developed models.

What You'll Do

  • Develop core LLM inference building blocks including Attention, MLP, Quantization, Speculative Decoding, and Mixture of Experts.
  • Optimize LLM inference performance on Neuron chips.
  • Adapt the latest research in LLM optimization to Neuron chips.
  • Work across teams and organizations with chip architects, compiler engineers, and runtime engineers.
  • Improve performance and accuracy across a range of models.

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Required

  • 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
  • Bachelor's degree in computer science or equivalent
  • 5+ years of programming using a modern programming language such as Java, C++, or C#, including object-oriented design experience
  • Fundamentals of Machine learning models, their architecture, training and inference lifecycles along with work experience on some optimizations for improving the model performance.

Preferred

  • Master's degree in computer science or equivalent
  • Hands-on experience with PyTorch or Jax - preferably involving developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware.

Original job description

Content provided by the employer

AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine
learning accelerators. This role is for a senior software engineer in the Machine Learning Inference Applications team. This role is responsible for development and performance optimization of core building blocks of LLM Inference - Attention, MLP, Quantization, Speculative Decoding, Mixture of Experts, etc.

The team works side by side with chip architects, compiler engineers and runtime engineers to deliver performance and accuracy on Neuron devices across a range of models.

Key job responsibilities
Responsibilities of this role include adapting latest research in LLM optimization to Neuron chips to extract best performance from both open source as well as internally developed models. Working across teams and organizations is key.

About the team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.

Basic Qualifications

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent
- 5+ years of programming using a modern programming language such as Java, C++, or C#, including object-oriented design experience
- Fundamentals of Machine learning models, their architecture, training and inference lifecycles along with work experience on some optimizations for improving the model performance.

Preferred Qualifications

- Master's degree in computer science or equivalent
- Hands-on experience with PyTorch or Jax - preferably involving developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware.

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.



USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually
amazon

About the company

amazon

Large Enterprise

Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.