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Amazon Applied Scientist Amazon Robotics AR 
United States, Washington, Seattle 
690233361

09.09.2024
DESCRIPTION

Key job responsibilities
- Research vision - Where should we be focusing our efforts in this rapidly developing field
- Research delivery – Proving/dis-proving strategies in offline data or in the lab to maximize progress and deliver results
- Production studies - Insights from production systems and dataA day in the life
Every day you will be interacting with scientists and engineers based in Seattle, Boston, and Arlington. You will be interfacing with engineers and scientists building and deploying production systems, and you will interact with the team managing our data lake. You will be connecting the dots by finding the most effective way to exploit our data to impact production. Communication is essential, as well as making quick decisions and moving ahead as quickly as possible to try out ideas, discard the ones that don’t work, and leaning into those that do.Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan

BASIC QUALIFICATIONS

- PhD, or Master's degree and 3+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Understanding of modern frameworks for foundation model training and model fine-tuning
- Ability to work both independently and with a team on ambiguous problems


PREFERRED QUALIFICATIONS

- Prior experience with vision or vision-language foundation models
- Exceptional ability to translate advances in the recent literature into concrete testable artifacts