Machine Learning Engineer

Who you are

You have a strong background in machine learning and experience with large-scale training pipelines — you've worked on projects involving the development and optimization of AI models, particularly in the context of generative AI. Your expertise includes fine-tuning Large Language Models (LLMs) for various applications, and you are familiar with tools like DeepSpeed and Fully Sharded Data Parallel (FSDP).

You possess a solid understanding of model optimization techniques, especially for deployment on specialized hardware such as AWS Inferentia and Trainium — your experience includes leveraging the AWS Neuron SDK and developing custom kernels to enhance model performance. You are comfortable working in a collaborative environment, engaging with multidisciplinary teams to deliver innovative AI solutions.

What you'll do

In this role, you will design and implement distributed training pipelines for LLMs, ensuring scalability and efficiency in the training process. You will be responsible for customizing and fine-tuning LLMs for diverse languages and domains, utilizing techniques such as continued pre-training and Reinforcement Learning with Human Feedback (RLHF).

You will collaborate closely with foundational model providers to optimize AI models specifically for Amazon Silicon, enhancing their performance and efficiency. Your work will involve tackling end-to-end LLM training pipelines at massive scale, delivering next-generation AI solutions for top AWS clients. You will also have the opportunity to innovate at the forefront of AI technology, contributing to transformative business opportunities across various industries.

What we offer

Amazon provides a dynamic work environment where you can engage with cutting-edge AI technologies and collaborate with a diverse team of experts. You will have the chance to work on impactful projects that shape the future of AI applications. We encourage you to apply even if your experience doesn't match every requirement, as we value diverse perspectives and backgrounds in our team.