Software Development Engineer AI/ML, Inference Serving, AWS Neuron

Software Development Engineer AI/ML, Inference Serving, AWS Neuron

AWS Neuron is the software stack powering AWS Inferentia and Trainium machine learning accelerators, designed to deliver high-performance, low-cost inference at scale. The Neuron Serving team develops infrastructure to serve modern machine learning models—including large language models (LLMs) and multimodal workloads—reliably and efficiently on AWS silicon. We are seeking a Software Development Engineer to lead and architect our next-generation model serving infrastructure, with a particular focus on large-scale generative AI applications.

Key job responsibilities

- Architect and lead the design of distributed ML serving systems optimized for generative AI workloads

- Drive technical excellence in performance optimization and system reliability across the Neuron ecosystem

- Design and implement scalable solutions for both offline and online inference workloads

- Lead integration efforts with frameworks such as vLLM, SGLang, Torch XLA, TensorRT, and Triton

- Develop and optimize system components for tensor/data parallelism and disaggregated serving

- Implement and optimize custom PyTorch operators and NKI kernels

- Mentor team members and provide technical leadership across multiple work streams

- Drive architectural decisions that impact the entire Neuron serving stack

- Collaborate with customers, product owners, and engineering teams to define technical strategy

- Author technical documentation, design proposals, and architectural guidelines

A day in the life

You'll lead critical technical initiatives while mentoring team members. You'll collaborate with cross‑functional teams of applied scientists, system engineers, and product managers to architect and deliver state‑of‑the‑art inference capabilities. Your day might involve:

- Leading design reviews and architectural discussions

- Rapidly prototyping software to show customer value

- Debugging complex performance issues across the stack

- Mentoring junior engineers on system design and optimization

- Collaborating with research teams on new ML serving capabilities

- Driving technical decisions that shape the future of Neuron's inference stack

About the team

The Neuron Serving team is at the forefront of scalable and resilient AI infrastructure at AWS. We focus on developing model‑agnostic inference innovations, including disaggregated serving, distributed KV cache management, CPU offloading, and container‑native solutions. Our team is dedicated to upstreaming Neuron SDK contributions to the open‑source community, enhancing performance and scalability for AI workloads. We're committed to pushing the boundaries of what's possible in large‑scale ML serving.

Recent shares:

https://awsdocs-neuron.readthedocs-hosted.com/en/latest/libraries/nxd-inference/developer_guides/disaggregated-inference.html

Basic Qualifications

- 5+ years of programming using a modern programming language such as Java, C++, or C#, including object‑oriented design 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

- 5+ years of non‑internship professional software development experience

- Experience as a mentor, tech lead or leading an engineering team

Preferred Qualifications

- Master's degree in computer science or equivalent

- Deep expertise in ML Frameworks/Libraries such as JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, TensorRT.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job‑related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign‑on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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