Amazon
1 week ago
Applied Scientist, AGI - Web & Knowledge Services
US, MA, Boston
Amazon's AGI Web & Knowledge Services group is seeking a passionate, talented, and inventive Applied Scientist to lead the development of industry-leading Information retrieval systems. As part of our AGI-IR team, you will play a pivotal role in developing efficient AI solutions for a multi-modal future at scale.
Key job responsibilities
- As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful conversations.
- Leverage Amazon's data and computing resources to accelerate advances in the state of the art.
- Work backwards from customer needs and use that information to make trade-offs between different modeling approaches
- Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems
- Report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment
- Drive best practices, helping to set high scientific and engineering standards on the team
- Promote the culture of experimentation and applied science at Amazon
Key job responsibilities
- As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful conversations.
- Leverage Amazon's data and computing resources to accelerate advances in the state of the art.
- Work backwards from customer needs and use that information to make trade-offs between different modeling approaches
- Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems
- Report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment
- Drive best practices, helping to set high scientific and engineering standards on the team
- Promote the culture of experimentation and applied science at Amazon
