Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization

Amazon is hiring a Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization in Seattle, United States. It pays $168k-$227k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
The listed pay starts close to the typical software engineer posting on Level.
Tools and skills the posting cites include Llama, Deepseek and PyTorch.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

llamadeepseekpytorchjaxstable-diffusion

Annapurna Labs designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.

AWS Neuron is the complete software stack for the AWS Trainium and Inferentia cloud-scale machine
learning accelerators and the Trn3/Trn2/Trn1 and Inf2/Inf1 servers that use them. This role is for a software engineer in the Distributed Training team for AWS Neuron. This role is responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive scale multi-modal large language models like Llama, Qwen, gpt-oss, DeepSeek and beyond, as well as multi-modal generation models such as Stable Diffusion, Flux, WAN, and many more.

The Distributed Training team works side by side with chip architects, compiler engineers and runtime engineers to create, build and tune distributed training solutions with AWS Trainium, maximize training throughput, minimize time-to-convergence, and push the boundaries of training efficiency on Trainium. You will identify and resolve performance bottlenecks across the stack, from collective communications and memory utilization to compiler optimizations and kernel performance.

Key job responsibilities
This role will lead efforts to optimize distributed training performance on Trainium, with a primary focus on maximizing training throughput, model flops utilization, and efficiency across the Neuron software stack. You will work across PyTorch, JAX, and the Neuron compiler and runtime to enable and tune large-scale training workloads on the latest Trainium instances.

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 non-internship professional software development experience
- - 5+ years of programming with at least one software programming language experience
- - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- - 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- - Experience as a mentor, tech lead or leading an engineering team

Preferred qualifications

- - Bachelor's degree in computer science or equivalent
- - Machine Learning knowledge in frameworks and end to end model training.

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

How we rate this

Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Sr. Software Engineer- AI/ML, AWS Neuron Distributed Training - Performance Optimization is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $168k-$227k a year.
The role is based in US, WA, Seattle.
The job was posted on May 21, 2025.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

LlamaDeepseekPyTorchJAXStable Diffusion

Also common in software engineer jobs at this level

Python C++AI agents Kubernetes Java Generative AI

Pay

This job starts at: $168k
Typical software engineer job: $168k

This posting starts close to the typical software engineer job. See software engineer jobs

Questions you could be asked

What's a project where you used Llama hands-on?
Walk me through how you've used Deepseek in your day-to-day work.
What are the limits of PyTorch that you've run into, and how did you work around them?
What's a project where you used JAX hands-on?
Walk me through how you've used Stable Diffusion in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Llama, Deepseek, PyTorch, JAX, and Stable Diffusion. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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