Sr. Software Engineer - AI/ML, AWS Neuron Inference - Multimodal

Sr. Software Engineer - AI/ML, AWS Neuron Inference - Multimodal

AWS Neuron is the complete software stack for the AWS Inferentia (Inf1/Inf2) and Trainium (Trn1), our cloud-scale Machine Learning accelerators. This role is for a machine learning engineer in the Inference team for AWS Neuron, responsible for development, enablement and performance tuning of a wide variety of ML model families, including massive-scale Large Language Models (LLM) such as GPT and Llama, as well as Stable Diffusion, Vision Transformers (ViT) and many more.

The ML Inference team works side by side with chip architects, compiler engineers and runtime engineers to create, build and optimize distributed inference solutions with Trainium/Inferentia instances. Experience with training and optimizing inference on these large models using Python/C++ is a must. Model parallelization, quantization, memory optimization - vLLM, DeepSpeed and other distributed inference libraries can be central to this and extending all of them for the Neuron based system is the key.

Key job responsibilities

You will help lead the efforts to build and achieve the best distributed training and inference performance of PyTorch, JAX, TensorFlow with XLA and other advanced frameworks on Neuron stacks. You will help optimize these models to ensure the highest performance and maximize the efficiency of them running on the custom AWS Trainium and Inferentia silicon and the Trn1, Inf1/2 servers. Strong software development (Python and C++) and Machine Learning knowledge (Multimodal, Computer Vision, Speech) are both critical to this role.

BASIC QUALIFICATIONS

1. Bachelor's degree in computer science or equivalent
2. 5+ years of non-internship professional software development experience
3. 5+ years of programming with at least one software programming language experience
4. 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
5. 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
6. Experience as a mentor, tech lead or leading an engineering team
7. Experience in machine learning, data mining, information retrieval, statistics or natural language processing

PREFERRED QUALIFICATIONS

1. Master's degree in computer science or equivalent
2. Experience in computer architecture
3. Previous software engineering expertise with Pytorch/Jax/Tensorflow, Distributed libraries and Frameworks, End-to-end Model Training.

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