Software Development Engineer, AI/ML, AWS Neuron, Model Inference
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.
Key Skills for This Role
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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