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.
Requirements
- 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)
- Hands-on experience with generative AI technology
- 1+ years experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework
Responsibilities
- Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency
- Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF)
- Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance
- Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions
Other
- 3+ years non-internship professional software development experience
- 2+ years non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 2+ years 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
- Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
