Amazon Machine Learning Engineer II Shopping Conversation Foundation 

United States, Washington, Seattle 

696405090

As a Machine Learning Engineer in this role, you will* Develop and maintain key services needed for evaluating and deploying large language models required for building conversational agents.
* Work with peers to investigate design approaches, prototype new technology and evaluate technical feasibility.
* Work closely with Applied scientists to process massive data, scale machine learning models while defining and optimizing criteria critical to the success of the customer experience
* Lead and influence the overall tech strategy by helping define data, enrichment, model optimizations and evaluation.
* Lead the system architecture, and spearhead the best practices that enable a quality infrastructure.
* Work in an Agile/Scrum environment to deliver high quality software against aggressive schedules.* Learn cutting-edge technologies and algorithms in the field of Generative AI advancing our journey to build the best conversational shopping agent.Key job responsibilities
- Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency
- LLM Customization & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF)
- Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK for enhanced performance

- 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
- Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference)

- 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
- 1+ years of experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework.