Machine Learning Engineer, Amazon Customer Service

Amazon • Seattle, WA

87d • $129,300 - $223,600

About The Position

Amazon Customer Service’s Shipping and Delivery Support (SDS) provides support to drivers who deliver packages to customers on behalf of Amazon. We are seeking a passionate and talented Machine Learning Engineer (MLE) to join our team in advancing state-of-the-art Generative AI technologies and Large Language Models (LLMs). In this role, you will design, develop, and deploy highly scalable AI models that benefit drivers, customer service associates, and customers. You will work closely with applied scientists and research teams to productionalize Machine Learning (ML) models, focusing on novel LLM training techniques, optimizations, and customization capabilities such as fine-tuning and distillation.

Requirements

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience programming with at least one software programming language
• 1+ years of machine learning, statistical modeling, data mining, and analytics techniques experience

Nice To Haves

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent
• Experience in machine learning, data mining, information retrieval, statistics or natural language processing

Responsibilities

• Collaborate with Applied Scientists to integrate state-of-the-art model architectures into the training pipeline, integrate state-of-the-art ML/LLM into CS system.
• Collaborate with Applied Scientists to process massive data, scale LLM while optimizing GPU utilization, memory management, and the training workflows (like offloading optimizer states, massive parallelization, etc).
• Cross-team collaboration to facilitate deployment and test of models in the production system.
• Design and maintain large-scale distributed training systems to support multi-modal foundation models.
• Optimize GPU utilization for efficient model training and fine-tuning on massive datasets.
• Develop robust monitoring and debugging tools to ensure the reliability and performance of training workflows, support piloting the LLMs and identify the related issues in the system.
• Collaborate with Engineers and Applied Scientists to investigate design approaches, prototype new LLM technique and evaluate technical feasibility, identify and solve complex problems.

Benefits

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Bachelor's degree