Software Engineer - AI/ML, AWS Neuron Apps

Amazon Web Services (AWS)

Seattle (WA)

On-site

USD 120,000 - 160,000

Full time

14 days+

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Job summary

A leading cloud services provider is seeking a Senior Software Engineer to join their Machine Learning Applications team in Seattle. This role involves developing and optimizing AI models at scale, focusing on distributed inference solutions and performance tuning for next-generation AI accelerators. Candidates should have strong programming skills in Python or C++, along with a solid foundation in machine learning. Competitive compensation is available.

Qualifications

  • 3+ years of experience in object-oriented design, data structures, algorithm design.
  • Experience with AI acceleration techniques including quantization and batching.
  • Fundamentals of machine learning and deep learning models.

Responsibilities

  • Drive the evolution of distributed AI at AWS Neuron.
  • Develop optimization bridges between ML frameworks and AI hardware.
  • Engineer performance optimizations for AWS Trainium and Inferentia.

Skills

Python
C++
ML framework internals
Distributed systems
Performance tuning

Education

Bachelor's degree in computer science or equivalent

Job description

Overview

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 Responsibilities
  • You will drive the evolution of distributed AI at AWS Neuron
  • You\'ll develop the bridge between ML frameworks including PyTorch, JAX and AI hardware. This isn\'t just about optimization—it's about revolutionizing how AI models run at scale.
  • 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 open-source ML communities and hardware architecture teams
Your Technical Arsenal
  • Deep expertise in Python and ML framework internals
  • Strong understanding of distributed systems and ML optimization
  • Passion for performance tuning and system architecture
Experience and Team Context

AWS Neuron focuses on distributed inference for AI workloads, with emphasis on large language model optimization, architecture-aware performance tuning, and scalable deployment.

Basic Qualifications
  • 3+ years of computer science fundamentals (object-oriented design, data structures, algorithm design, problem solving and complexity analysis)
  • 3+ years of programming experience using Python or C++ and PyTorch
  • Experience with AI acceleration via quantization, parallelism, model compression, batching, KV caching, vllm serving
  • Experience with accuracy debugging & tooling, performance benchmarking of AI accelerators
  • Fundamentals of machine learning and deep learning models, their architecture, training and inference lifecycles, with work experience on optimizations for improving model execution
Preferred Qualifications
  • Bachelor\'s degree in computer science or equivalent

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require a workplace accommodation during the application and hiring process, including support for the interview or onboarding, please visit the accommodations page.

Our compensation reflects the cost of labor across US geographic markets. The base pay ranges and other compensation details are provided for context. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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