Amazon Web Services, Inc.
Technology
SrMachineLearningEngineer,GenerativeAIInnovationCenter
Neural analysis suggests this role is
optimal for Senior candidates.
“Sr Machine Learning Engineer, Generative AI Innovation Center at Amazon Web Services, Inc.. Skills: Generative AI, Large Language Models, LLM training, Model optimization. Drive LLM development. Fine-tune LLMs”
Industry & Context.
Tackle end-to-end LLM pipelines
What They're Looking For.
Must Have
4+ years software development experience, 4+ years programming experience, 4+ years leading design/architecture, Experience as mentor or tech lead, Hands-on deep learning experience, Hands-on machine learning experience, Hands-on generative AI experience
Nice to Have
5+ years full SDLC experience, Bachelor's degree in computer science
What You'll Do.
Drive LLM development
Optimize models for deployment
Design distributed training pipelines
Implement distributed training pipelines
Adapt LLMs for new languages
Adapt LLMs for new domains
Adapt LLMs for vision applications
Optimize AI models on AWS Silicon
Develop custom kernels
Interact with enterprise customers
Interact with model providers
Co-develop generative AI solutions
How You'll Work.
Team & Collaboration
Multidisciplinary team; Customer collaboration; Foundational model providers
Full Job Description
The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency. As a software development engineer (SDE) on our team, you will drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS’s custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation AI solutions for top AWS clients. 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 and developing custom kernels for enhanced performance - Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions About the team ABOUT AWS: Diverse Experiences Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the
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