About the job
The Amazon AGI SF Lab is focused on developing new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds. In other words, we’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled. The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Our philosophy combines the agility of a startup with the resources of Amazon. By keeping the team lean, we’re able to maximize the amount of compute per person. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research.
Responsibilities
Develop multimodal Large Language Models (LLMs) to observe, model and derive insights from manual workflows for automation
Work in a joint scrum with engineers for rapid invention, develop automation agent systems, and take them to launch for millions of customers
Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI
Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results
Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems
Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports
Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team
Qualifications
Minimum
PhD, or Master's degree and 5+ years of applied research experience
3+ years of building machine learning models for business application experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning
Preferred
PhD in Computer Science, Machine Learning, or a related field, with a focus on Gen AI and reinforcement learning
Demonstrated experience in developing and implementing algorithms and models for supervised fine-tuning and reinforcement learning through human feedback
Strong programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch
Excellent problem-solving skills, with the ability to think creatively and critically about complex problems
Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
Experience with patents or publications at top-tier peer-reviewed conferences or journals