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

Amazon Web Services
Seattle, USA
Full-time
Onsite
USD 165200-223600 yearly
Discovered 3 weeks ago
PythonC++Machine learningLarge language modelsDistributed inferenceSystem performance optimization

Full Job Posting

Role overview

Join AWS Annapurna Labs to develop the Neuron SDK, which accelerates deep-learning and generative AI workloads on Inferentia and Trainium.

Work across machine-learning frameworks, kernels, compilers, runtimes, and hardware to improve high-performance inference and model enablement.

The role focuses on distributed inference and tuning large LLM families for performance on AWS custom accelerators.

Responsibilities

  • Build distributed inference support for PyTorch in the Neuron SDK and tune models for performance and efficiency on Trainium and Inferentia.
  • Design and optimize models, frameworks, kernels, and ML operation features for custom accelerators.
  • Contribute to distributed system architecture, implementation, profiling, hardware-specific optimization, testing, and production deployment.
  • Build infrastructure to analyze and onboard models with diverse architectures.
  • Optimize across Neuron hardware generations and implement fusion, sharding, tiling, and scheduling techniques.
  • Test models, support continuous releases, and work with customers to enable and optimize their workloads.
  • Collaborate across compiler, runtime, framework, and hardware teams; debug issues and improve memory usage and software systems.

Basic qualifications

  • Bachelor's degree in computer science or equivalent; at least 3 years of non-internship professional software development experience.
  • At least 3 years designing or architecting systems, including design patterns, reliability, and scaling.
  • Knowledge of machine learning and LLM architecture, training and inference lifecycles, and model execution optimization.
  • Software development experience in at least one of C++ or Python.
  • Strong understanding of system performance, memory management, parallel computing, computer architecture, and operating-systems-level software.
  • Proficiency in debugging, profiling, and software engineering practices for large-scale systems.

Preferred qualifications

  • Master's degree or Ph.D. in Computer Science or equivalent.
  • Familiarity with PyTorch, JIT compilation, AOT tracing, CUDA or equivalent low-level kernels, and Triton-like tile semantics.
  • Performant kernel development such as CUTLASS or FlashInfer is relevant.
  • Experience with production inference serving platforms such as vLLM, SGLang, TensorRT, or similar.

Compensation

  • Annual base salary is USD 165,200–223,600 for the listed Cupertino location; compensation may also include sign-on payments and restricted stock units.

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