Applied Scientist, Amazon Legal technologies

Seattle, Washington, USA

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Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges across Amazon's varied businesses? If so, Amazon's Legal technologies team has an exciting opportunity for you as an Applied Scientist.
At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Amazon Legal technologies team plays a pivotal role in supporting all Amazon Businesses and solving complex customer problems.
As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers. You will be part of a global team that is focused on solving both Legal and business problems. The position is based in Seattle but will interact with global customers and teams.
Join us at Amazon Legal tech and you would have the opportunity to solve some the most complex problems surrounding the Legal industry.
Please visit https://www.amazon.science for more information

Key job responsibilities
Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges.
Collaborate with cross-functional teams, including software engineers, applied scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions.
Continuously explore and evaluate state-of-the-art NLP techniques and methodologies to improve the accuracy and efficiency of language-related systems.
Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact.

Basic Qualifications


- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse

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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,400/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.

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Category: Data Science Jobs

Tags: Data warehouse Java LLMs Machine Learning NLP Oracle Python RDBMS SQL

Perks/benefits: Career development Conferences Equity / stock options

Region: North America
Country: United States

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