Senior Software Development Engineer, AI/ML, AWS Neuron, Model Inference

Amazon; Cupertino (CA); On-site; USD 193,300 - 261,500; Full time

Job summary

Amazon Web Services is seeking a Senior Software Development Engineer to advance AI/ML inference on Neuron accelerators. You will design, optimize, and deploy ML models and kernels, participate in end‑to‑end system development, and work across frameworks and hardware boundaries to maximize performance for GenAI workloads.

Join a team focused on cutting‑edge architecture, profiling, and production deployment, collaborating with customers and open‑source communities to push the frontier of AI

Qualifications

• Bachelor’s degree in computer science or equivalent.
• 5+ years of non‑internship professional software development experience.
• 5+ years of non‑internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
• Fundamentals of machine learning and LLMs, their architecture, training and inference lifecycles along with work experience on some optimizations for improving model execution.
• Software development experience in C++ and Python (experience in at least one language is required).
• Strong understanding of system performance, memory management, and parallel computing principles.
• Proficiency in debugging, profiling, and implementing best software engineering practices in large‑scale systems.

Responsibilities

• Design, develop, and optimize machine learning models and frameworks for deployment on custom ML hardware accelerators.
• Participate in all stages of the ML system development lifecycle, including distributed computing architecture design, implementation, performance profiling, hardware‑specific optimizations, testing, and production deployment.
• Build infrastructure to systematically analyze and onboard multiple models with diverse architecture.
• Design and implement high-performance kernels and features for ML operations, leveraging the Neuron architecture and programming models.
• Analyze and optimize system‑level performance across multiple generations of Neuron hardware.
• Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks.
• Implement optimizations such as fusion, sharding, tiling, and scheduling.
• Conduct comprehensive testing, including unit and end‑to‑end model testing with continuous deployment and releases through pipelines.
• Work directly with customers to enable and optimize their ML models on AWS accelerators.
• Collaborate across teams to develop innovative optimization techniques.

Skills

C++

Python

Performance optimization

Parallel computing

Debugging & profiling

Education

Bachelor's degree in CS or equivalent

Master’s degree in CS or equivalent

Tools

PyTorch

JIT compilation

AOT tracing

CUDA kernels

CUTLASS

TensorRT

Triton

Job description

Senior Software Development Engineer, AI/ML, AWS Neuron, Model Inference

The Annapurna Labs team at Amazon Web Services (AWS) builds AWS Neuron, the software development kit used to accelerate deep learning and GenAI workloads on Amazon’s custom machine learning accelerators, Inferentia and Trainium. The AWS Neuron SDK, developed by the Annapurna Labs team, is the backbone for accelerating deep learning and GenAI workloads on Amazon's Inferentia and Trainium ML accelerators. It includes an ML compiler, runtime, and application framework that seamlessly integrates with popular ML frameworks like PyTorch and JAX, enabling unparalleled ML inference and training performance.

The Inference Enablement and Acceleration team runs a wide range of models and supports novel architecture while maximizing performance for AWS's custom ML accelerators. Working across the stack from PyTorch to the hardware-software boundary, engineers build systematic infrastructure, innovate new methods and create high-performance kernels for ML functions. They combine deep hardware knowledge with ML expertise to push the boundaries of AI acceleration.

As part of the broader Neuron organization, the team works across multiple technology layers—frameworks, kernels, and compiler to runtime—and collaborates with collectives. They not only optimize current performance but also contribute to future architecture designs, working closely with customers to enable their models and ensure optimal performance. This role offers a unique opportunity to work at the intersection of machine learning, high‑performance computing, and distributed architectures.

Posted: May 24, 2026 (Updated about 14 hours ago)

Key job responsibilities

• Design, develop, and optimize machine learning models and frameworks for deployment on custom ML hardware accelerators.
• Participate in all stages of the ML system development lifecycle, including distributed computing architecture design, implementation, performance profiling, hardware‑specific optimizations, testing, and production deployment.
• Build infrastructure to systematically analyze and onboard multiple models with diverse architecture.
• Design and implement high-performance kernels and features for ML operations, leveraging the Neuron architecture and programming models.
• Analyze and optimize system‑level performance across multiple generations of Neuron hardware.
• Conduct detailed performance analysis using profiling tools to identify and resolve bottlenecks.
• Implement optimizations such as fusion, sharding, tiling, and scheduling.
• Conduct comprehensive testing, including unit and end‑to‑end model testing with continuous deployment and releases through pipelines.
• Work directly with customers to enable and optimize their ML models on AWS accelerators.
• Collaborate across teams to develop innovative optimization techniques.

A day in the life

You will collaborate with a cross‑functional team of applied scientists, system engineers, and product managers to deliver state‑of‑the‑art inference capabilities for Generative AI applications. Your work will involve debugging performance issues, optimizing memory usage, and shaping the future of Neuron's inference stack across Amazon and the Open Source Community. You will create metrics, implement automation, and resolve the root cause of software defects while building high‑impact solutions for a large customer base. You will participate in design discussions, code reviews, and communicate with internal and external stakeholders in a startup‑like development environment.

About the team

The Inference Enablement and Acceleration team fosters a builder’s culture where experimentation is encouraged and impact is measurable. They emphasize collaboration, technical ownership, and continuous learning. Mentorship is a core practice; senior members provide one‑on‑one guidance and thorough, kind code reviews. The team supports new members and celebrates knowledge sharing.

Basic Qualifications

• Bachelor’s degree in computer science or equivalent.
• 5+ years of non‑internship professional software development experience.
• 5+ years of non‑internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
• Fundamentals of machine learning and LLMs, their architecture, training and inference lifecycles along with work experience on some optimizations for improving model execution.
• Software development experience in C++ and Python (experience in at least one language is required).
• Strong understanding of system performance, memory management, and parallel computing principles.
• Proficiency in debugging, profiling, and implementing best software engineering practices in large‑scale systems.

Preferred Qualifications

• Master’s degree in computer science or equivalent.
• 5+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
• Familiarity with PyTorch, JIT compilation, and AOT tracing.
• Familiarity with CUDA kernels or equivalent ML or low‑level kernels.
• Experience with performant kernel development such as CUTLASS, FlashInfer, etc.
• Familiarity with syntax and tile‑level semantics similar to Triton.
• Experience with online/offline inference serving with vLLM, SGLang, TensorRT or similar platforms in production environments.
• Deep understanding of computer architecture, operating systems level software, and working knowledge of parallel computing.

Salary and benefits

The base salary range for this position is USD 193,300.00 – 261,500.00 annually, based in Cupertino, CA. Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on experience, qualifications, and location. Amazon also offers comprehensive benefits, including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and optional 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.

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 include working safely and cooperatively with other employees, supervisors, and staff; adhering to standards of excellence; communicating effectively and respectfully; and following 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. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.