Amazon Sr Business Development Manager Amazon Services 

United States, Washington, Seattle 

103408304

As an 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

- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Hands-on experience with deep learning and machine learning methods (e.g., for training, fine tuning, and inference)
- Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies

- Bachelor's degree in Computer Science or equivalent
- Hands-on experience with at least one ML library or framework
- 2+ years of experience in developing, deploying or optimizing ML models
- 5+ years of experience in the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations