Description

Amazon is seeking a dynamic Entry-Level Applied Scientist to join our Search Experience Science team, which is pioneering the future of AI-driven shopping experiences. This role is ideal for candidates passionate about large language models and their application in enhancing user engagement through advanced AI technologies. You will be part of a highly scientific and engineering-driven group dedicated to innovating AI technologies for the customer experiences of Amazon's AI shopping assistant (Rufus).

Key job responsibilities

1. Collaborate with senior scientists to prototype AI solutions that enhance multi-turn conversations and deepen user intent understanding.

2. Design and implement scalable methods for collecting and analyzing customer feedback, utilizing this data to refine and personalize the shopping experience.

3. Develop and optimize policies using reinforcement learning and other advanced methods to continuously improve the performance and user satisfaction of our AI systems.

4. Contribute to a culture of innovation and publish findings in top-tier scientific venues, with encouragement to continue publishing groundbreaking research in relevant fields.

A day in the life

1. Research and Development:

Fine-tune large language models and prototype algorithms for multi-turn conversations.

2. Collaboration and Feedback:

Work with engineers, product managers, and UX designers. Collect and analyze user feedback to refine AI responses.

3. Implementation and Reporting:

Apply policy optimization methods like reinforcement learning. Monitor AI performance and document developments.

4. Stakeholders:

Senior scientists, engineers, product managers, UX designers.

5. Customers:

Amazon search and shopping users.

6. Goals:

Enhance user intent understanding, personalize experiences, and increase engagement.

About the team

You will become part of a dynamic team comprising over 100 scientists and engineers focused on shaping the future of AI-driven shopping experiences at Amazon. This team works on every aspect of the shopping experience, from understanding user queries and planning retrievals to generating answers and delivering outstanding customer service. Additionally, the team works on enhancing Amazon Search by improving query comprehension, mission-aware search strategies, navigation, and more.

We are open to hiring candidates to work out of one of the following locations:

Palo Alto, CA, USA

Basic Qualifications

• Experience programming in Java, C++, Python or related language

• Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

• Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field

Preferred Qualifications

• Experience implementing algorithms using both toolkits and self-developed code

• Have publications at top-tier peer-reviewed conferences or journals

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $115,100/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.