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Aws Neuron Apps Jobs (NOW HIRING)

Amazon

Sr. Software Engineer- AI/ML, AWS Neuron Apps

Seattle, WA · On-site

$139.40K - $183.80K/yr

Shape the Future of AI Accelerators at AWS Neuron Join the elite team behind AWS Neuron-the software stack powering AWS's next-generation AI accelerators Inferentia and Trainium. As a Senior Software ...

Amazon

Sr. Software Engineer- AI/ML, AWS Neuron Apps

Seattle, WA · On-site

$139.40K - $183.80K/yr

Shape the Future of AI Accelerators at AWS Neuron Join the elite team behind AWS Neuron-the software stack powering AWS's next-generation AI accelerators Inferentia and Trainium. As a Senior Software ...

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How much do aws neuron apps jobs pay per hour?

As of May 30, 2026, the average hourly pay for aws neuron apps in the United States is $70.06, according to ZipRecruiter salary data. Most workers in this role earn between $62.26 and $81.73 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AWS Neuron Apps Developer, and why are they important?

To thrive as an AWS Neuron Apps Developer, you need a strong background in machine learning frameworks (like TensorFlow or PyTorch), Python programming, and a solid understanding of AWS infrastructure, often supported by relevant AWS certifications. Familiarity with AWS Neuron SDK, Inferentia and Trainium hardware, and cloud deployment tools is essential. Strong problem-solving abilities, adaptability, and effective communication help you collaborate and optimize AI workloads efficiently. These skills are crucial for building, deploying, and scaling high-performance AI applications on AWS, ensuring both technical excellence and cost-effectiveness.

What are some common challenges faced when developing applications with AWS Neuron, and how can a new team member effectively overcome them?

Developing applications with AWS Neuron often involves optimizing deep learning models to run efficiently on Inferentia or Trainium hardware, which can present challenges with model compatibility, debugging, and performance tuning. New team members can overcome these hurdles by familiarizing themselves with the Neuron SDK, leveraging AWS-provided tools for profiling and debugging, and collaborating closely with cloud infrastructure and machine learning teams. Regularly reviewing Neuron release notes and documentation ensures awareness of the latest features and best practices, helping to streamline the deployment process and maximize performance.

What are AWS Neuron Apps?

AWS Neuron Apps refer to applications that are specifically designed and optimized to run on AWS Inferentia and Trainium chips using the AWS Neuron SDK. These apps leverage Neuron's machine learning acceleration to deliver high-performance deep learning inference and training, often at lower costs compared to traditional GPU-based solutions. Developers can use popular frameworks like TensorFlow and PyTorch with Neuron to build, deploy, and scale AI workloads efficiently on AWS infrastructure.

What is the difference between Aws Neuron Apps vs AWS Cloud Engineers?

AspectAws Neuron AppsAWS Cloud Engineers
Primary FocusDeveloping and optimizing machine learning inference applications on AWSDesigning, deploying, and managing cloud infrastructure and services on AWS
Required SkillsMachine learning, AWS Neuron SDK, programming (Python, C++)Cloud architecture, scripting, security, networking
Work EnvironmentData centers, AI/ML labs, software development teamsCloud environments, DevOps teams, infrastructure management
CertificationsAWS Certified Machine Learning – Specialty, AWS Certified Solutions ArchitectAWS Certified Solutions Architect, AWS Certified DevOps Engineer

While Aws Neuron Apps focus on deploying machine learning inference workloads using AWS Neuron SDK, AWS Cloud Engineers handle broader cloud infrastructure and services. Both roles require AWS certifications and technical expertise but differ in their core responsibilities and work environments.

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Infographic showing various Aws Neuron Apps job openings in the United States as of May 2026, with employment types broken down into 25% Locum Tenens, 25% As Needed, and 50% Part Time. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $145,725 per year, or $70.1 per hour.
Sr. Software Engineer- AI/ML, AWS Neuron Apps

Sr. Software Engineer- AI/ML, AWS Neuron Apps

Amazon

Seattle, WA • On-site

$139.40K - $183.80K/yr

Full-time

Posted 4 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,788 frontline employees who took The Breakroom Quiz

7th of 39 rated national retailers

Job description

Shape the Future of AI Accelerators at AWS Neuron
Join the elite team behind AWS Neuron-the software stack powering AWS's next-generation AI accelerators Inferentia and Trainium. As a Senior Software Engineer in our Machine Learning Applications team, you'll be at the forefront of deploying and optimizing some of the world's most sophisticated AI models at unprecedented scale.
What You'll Impact:
Pioneer distributed inference solutions for industry-leading LLMs such as GPT, Llama, Qwen
Optimize breakthrough language and vision generative AI models
Collaborate directly with silicon architects and compiler teams to push the boundaries of AI acceleration
Drive performance benchmarking and tuning that directly impacts millions of inference calls globally
Key job responsibilities
You will drive the Evolution of Distributed AI at AWS Neuron
As a Technical Leader at the forefront of AWS's AI Accelerator, you'll architect the bridge between ML frameworks including PyTorch, JAX and AI hardware. This isn't just about just optimization-it's about revolutionizing how AI models run at scale.
Technical Impact You'll Drive:
Spearhead distributed inference architecture for PyTorch and JAX using XLA
Engineer breakthrough performance optimizations for AWS Trainium and Inferentia
Develop ML tools to enhance LLM accuracy and efficiency
Transform complex tensor operations into highly optimized hardware implementations
Pioneer benchmarking methodologies that shape next-gen AI accelerator design
What Makes This Role Unique:
Direct influence on AWS's AI infrastructure used by thousands of ML applications
Full-stack optimization from high-level frameworks to hardware-specific primitives
Creation of tools and frameworks that define industry standards for ML deployment
Collaboration with both open-source ML communities and hardware architecture teams
Your Technical Arsenal Should Include:
Deep expertise in Python and ML framework internals
Strong understanding of distributed systems and ML optimization
Passion for performance tuning and system architecture
A day in the life
Work/Life Balance
Our team puts a high value on work-life balance

It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.
About the team
At AWS Neuron, we're revolutionizing how the world's most sophisticated AI models run at scale through Amazon's next-generation AI accelerators. Operating at the unique intersection of ML frameworks and custom silicon, our team drives innovation from silicon architecture to production software deployment.
We pioneer distributed inference solutions for PyTorch and JAX using XLA, optimize industry-leading LLMs like GPT and Llama, and collaborate directly with silicon architects to influence the future of AI hardware

Our systems handle millions of inference calls daily, while our optimizations directly impact thousands of AWS customers running critical AI workloads.
We're focused on pushing the boundaries of large language model optimization, distributed inference architecture, and hardware-specific performance tuning. Our deep technical experts transform complex ML challenges into elegant, scalable solutions that define how AI workloads run in production.

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About Amazon

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Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US

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