Massachusetts Green Jobs

Description

The AI Domains org within the Alexa Conversational Assistants Services (CAS) org is looking for a Senior Applied Scientist with a background in Natural Language Processing, Machine/Deep Learning, and Large Language Models (LLMs). You will be working with a team of applied and research scientists to enhance existing features and explore new possibilities with LLM empowerment. You will own high visibility programs with broad visibility and global impact. You will interact with a cross-functional team of science, product, and engineering leaders.

We are looking for Senior Applied Science Manager who will play a key role in the next generation of AI powered Conversational Assistants.

Key job responsibilities

Lead and manage a team of applied and research scientists, and language engineers, data linguists responsible for building conversational assistants

Collaborate with cross-functional teams to ensure that Amazon’s AI models are aligned with human preferences.

Identify and prioritize research opportunities that have the potential to significantly impact our AI systems.

Mentor and guide team members to achieve their career goals and objectives.

Communicate research findings and progress to senior leadership and stakeholders.

Rapidly experiment and drive productization to deliver customer impact

About the team

The AI Domains (AIDo) team's vision is to build world-class AI-based services to improve conversational CX across endpoints, modalities, and locales. Our leading solutions empower Domains and Horizontal CX owners to rapidly scale and optimize their experiences. We are part of the Conversational Assistant Services (CAS) org, the Sciences org that builds and maintains products such as Alexa. We are pioneering Gen AI revolution rapidly iterating to deliver high quality Gen AI enabled customer experience. Come join us to the invent the future for our customers!

Basic Qualifications

• Masters in Computer Science, Linguistics, or a related field.

• 10+ years experience in natural language processing, machine learning, or a related field.

• Proven track record of leading and managing science teams that deliver large impact.

• Expert knowledge of machine learning algorithms and techniques.

• Familiarity with large-scale data processing and storage systems.

• Excellent communication and interpersonal skills.

• Ability to work in a fast-paced, collaborative environment

Preferred Qualifications

PHD and Experience with building applications using Large language models

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 $196,900/year in our lowest geographic market up to $340,300/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.