Software Development Engineer I, Inference models optimization, AWS Neuron Inference

Amazon is hiring a Software Development Engineer I, Inference models optimization, AWS Neuron Inference in Cupertino, United States. It pays $127k-$185k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this software engineer role Builds AI ●●●●: the job is building AI systems.
Tools and skills the posting cites include vLLM, PyTorch and JAX.
Level lists 20,000+ other open roles at Amazon.
The role was posted in the last few days.

AI in this role

vLLMPyTorchJAX

The Annapurna Labs team at Amazon Web Services (AWS) builds the AWS Neuron SDK, the software development kit used to accelerate deep learning and GenAI workloads on AWS Trainium machine learning accelerators.

The Neuron Inference organization is at the forefront of optimizing inference performance for a wide range of ML models and model architectures on AWS's custom ML accelerators. We are working across the stack from PyTorch to the hardware-software boundary, our engineers build systematic infrastructure, develop high-performance kernels for ML functions, ensuring every compute unit is fine-tuned for optimal performance for our customers' demanding workloads. We combine deep hardware knowledge with ML expertise to push the boundaries of what's possible in AI acceleration.

As part of the broader Neuron organization, our team works across multiple technology layers — from frameworks and kernels through to compiler, runtime, and collectives. We not only optimize performance on open weight models but also contribute to future architecture designs and work closely with customers to enable optimal performance on their models. This role offers a unique opportunity to work at the intersection of machine learning, high-performance computing, and distributed architectures, where you'll help shape the future of AI acceleration technology.

As a Software Engineer I, you will design and implement business-critical features and contribute to optimizing the performance of models on AWS Trainium end to end. We operate in spaces that are very large, yet our teams remain small and agile. There is no blueprint. We're inventing. We're experimenting. It is a very unique learning culture. The team works closely with customers on their model enablement, providing direct support and optimization expertise to ensure their machine learning workloads achieve optimal performance on AWS ML accelerators. The team also collaborates with open source ecosystems to provide seamless integration and bring peak performance at scale for customers and developers.

This role is responsible for development, enablement, and performance tuning of a wide variety of LLM model families, including massive-scale large language models like GLM, Kimi, and beyond. The Model Enablement team works side by side with compiler engineers and runtime engineers to create, build, and tune distributed inference solutions with AWS Trainium.

You can learn more about Neuron:

* https://awsdocs-neuron.readthedocs-hosted.com/en/latest/compiler/index.html
* https://aws.amazon.com/machine-learning/neuron/
* https://github.com/aws/aws-neuron-sdk
* https://github.com/vllm-project/vllm-neuron
* https://www.amazon.science/how-silicon-innovation-became-the-secret-sauce-behind-awss-success

If this sounds exciting to you - come build the future with us!

Key job responsibilities
* Optimize open models to run best on Trainium, including optimizing sharding, developing NKI kernels and ensuring accuracy. This provides ready-to-serve models to our customers and also gives them a starting point to optimize their own.
* Collaborate with cross-disciplinary teams that may include hardware design, firmware, compiler, runtime, and ML engineers to develop software that enables and optimizes custom ML accelerator silicon
* Write clean, maintainable code (C/C++, Python, or Rust) following best practices for systems-level and performance-critical development
* Participate in code reviews, contribute to technical documentation, and help deploy agentic tools to accelerate the enablement of new models on Trainium
* Demonstrate operational excellence through monitoring, debugging, and resolving issues across hardware-software integration boundaries, including on-call responsibilities
* Keep learning emerging technologies in ML accelerators, compiler optimization, computer architecture, and cloud-scale distributed systems

About the team
The Model Enablement team fosters a builder's culture where experimentation is encouraged and impact is measurable. We emphasize collaboration, technical ownership, and continuous learning.
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 that help our team members develop their engineering expertise so they feel empowered to take on more complex tasks in the future. Join us to solve some of the most interesting and impactful infrastructure challenges in AI/ML today.
Our team builds and operates software that powers key experiences for Amazon customers. We value technical excellence, collaboration, and a commitment to continuous improvement. Every engineer on the team has a voice in shaping our technical direction and the opportunity to mentor others.
We are focused on building reliable, scalable systems while creating an inclusive environment where engineers at all levels can learn, grow, and do their best work. If you want to solve meaningful problems alongside a supportive and motivated group of engineers, this is the place for you.

Basic qualifications

- Experience with data structure implementation, basic algorithm development, and/or object-oriented design principles
- Currently has, or is in the process of obtaining, a Bachelor's degree or above in Computer Science, Computer Engineering, Electrical Engineering, or related fields
- Experience with any programming language such as Python, Java, C++

Preferred qualifications

- Experience from previous technical internship(s) or demonstrated project experience
- Experience with one or more of the following: compiler design or optimization, computer architecture, hardware simulation or emulation, ML frameworks (PyTorch, JAX), performance profiling and analysis, Linux kernel or embedded systems, AI tools for development productivity, cloud platforms (preferably AWS), version control systems
- Strong problem-solving skills with ability to debug across hardware-software boundaries
- Demonstrated ability to learn and adapt to new technologies quickly

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, Cupertino - 127,100.00 - 185,000.00 USD annually

How we rate this

Software Development Engineer I, Inference models optimization, AWS Neuron Inference at Amazon rates 92 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

Software Development Engineer I, Inference models optimization, AWS Neuron Inference is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $127k-$185k a year.
The role is based in US, CA, Cupertino.
The job was posted on November 10, 2026.
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

vLLMPyTorchJAX

Also common in software engineer jobs at this level

AI agents Kubernetes TypeScript RAG Google Cloud Docker

Pay

This job starts at: $127k
Typical software engineer job: $167k

This posting starts 24% below the typical software engineer job. See software engineer jobs

Questions you could be asked

What's a project where you used vLLM hands-on?
Walk me through how you've used PyTorch in your day-to-day work.
What are the limits of JAX that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: vLLM, PyTorch, and JAX. 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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