Amazon Applied Scientist AGI - Neural Efficiency Science 

United States, Pennsylvania, Pittsburgh 

426589804

- Pioneer new approaches to foundation models
- Publish and present research at top-tier conferences and journals
- Work with state-of-the-art LLMs and multi-modal foundation models
- Access to substantial computational resources for researchKey job responsibilities
- Research and develop novel techniques for efficient runtime inference (low latency, high throughput)
- Design and evaluate efficient foundation model architectures
- Create new methods for improving training efficiency
- Conduct experimental studies to validate efficiency improvements
- Write high-quality Python code to implement research ideas- Author technical documentation and research papers
- Present findings to technical and non-technical stakeholders
A day in the life
Your day might start with a team stand-up to discuss ongoing projects and brainstorm solutions to technical challenges. You'll spend time implementing and testing new efficiency optimization techniques in Python, analyzing performance metrics, and iterating on approaches. You'll collaborate with team members to review code and research results, participate in technical discussions about architecture designs, and engage with other AGI teams to understand their efficiency needs. You might end your day analyzing experimental results or writing up findings for a research paper. Throughout the week, you'll have opportunities to present your work to stakeholders and contribute to the team's research roadmap.

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing