Applied Scientist, Alexa Enterprise
Job Description
Are you looking for an opportunity to build an LLM-based enterprise-grade, highly available, large scale solution? Does it excite you to find patterns and build generic, composable solutions to solve complex problems? Are you looking for inventing newer and simpler ways of building solutions? If so, we are looking for you to fill a challenging position in Alexa Enterprise (AE) team. AE brings the power of Alexa voice assistant to enterprise partners in industries such as hospitality and senior living. We tackle pressing challenges like workforce shortage. We are inventing Large Language Models (LLM)-driven interactions to create memorable moments for users while simultaneously boosting partner revenues and reinforcing brand identity. Beyond managed properties, AE extends Alexa's reach to premium third-party devices, seamlessly integrating with household names like Samsung, LG, and Sonos, thus amplifying its impact across diverse ecosystems.AE team is looking for a passionate, highly skilled and inventive Applied Scientist, with a strong machine learning background, to lead the development and implementation of state-of-the-art ML systems for Alexa Enterprise use cases. As an Applied Scientist in the team, you will play a critical role in driving the development of conversational assistants, in particular those based on Large Language Models (LLM's), that meet enterprise standards. You will handle Amazon-scale use cases with significant impact on our customers' experiences.Key job responsibilities- You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence- You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases- Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints- Create, innovate, and deliver deep learning, policy-based learning, and/or machine learning-based algorithms to deliver customer-impacting results- Perform model/data analysis and monitor metrics through online A/B testing
Locations
- United States, WA, Seattle, Seattle, WA, United States
- United States, WA, Bellevue, Bellevue, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
180,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of building models for business application experienceintermediate
- - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experienceintermediate
- - Experience programming in Java, C++, Python or related languageintermediate
- - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computingintermediate
Required Qualifications
- - 3+ years of building models for business application experience (experience, 3 years)
- - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience (experience, 4 years)
- - Experience programming in Java, C++, Python or related language (experience)
- - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing (experience)
Preferred Qualifications
- - Experience using Unix/Linux (experience)
- - Experience in professional software development (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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. (experience)
Responsibilities
- - You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence
- - You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases
- - Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints
- - Create, innovate, and deliver deep learning, policy-based learning, and/or machine learning-based algorithms to deliver customer-impacting results
- - Perform model/data analysis and monitor metrics through online A/B testing
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Tags & Categories
Applied Scientist, Alexa Enterprise
Job Description
Are you looking for an opportunity to build an LLM-based enterprise-grade, highly available, large scale solution? Does it excite you to find patterns and build generic, composable solutions to solve complex problems? Are you looking for inventing newer and simpler ways of building solutions? If so, we are looking for you to fill a challenging position in Alexa Enterprise (AE) team. AE brings the power of Alexa voice assistant to enterprise partners in industries such as hospitality and senior living. We tackle pressing challenges like workforce shortage. We are inventing Large Language Models (LLM)-driven interactions to create memorable moments for users while simultaneously boosting partner revenues and reinforcing brand identity. Beyond managed properties, AE extends Alexa's reach to premium third-party devices, seamlessly integrating with household names like Samsung, LG, and Sonos, thus amplifying its impact across diverse ecosystems.AE team is looking for a passionate, highly skilled and inventive Applied Scientist, with a strong machine learning background, to lead the development and implementation of state-of-the-art ML systems for Alexa Enterprise use cases. As an Applied Scientist in the team, you will play a critical role in driving the development of conversational assistants, in particular those based on Large Language Models (LLM's), that meet enterprise standards. You will handle Amazon-scale use cases with significant impact on our customers' experiences.Key job responsibilities- You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence- You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases- Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints- Create, innovate, and deliver deep learning, policy-based learning, and/or machine learning-based algorithms to deliver customer-impacting results- Perform model/data analysis and monitor metrics through online A/B testing
Locations
- United States, WA, Seattle, Seattle, WA, United States
- United States, WA, Bellevue, Bellevue, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
180,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of building models for business application experienceintermediate
- - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experienceintermediate
- - Experience programming in Java, C++, Python or related languageintermediate
- - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computingintermediate
Required Qualifications
- - 3+ years of building models for business application experience (experience, 3 years)
- - PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience (experience, 4 years)
- - Experience programming in Java, C++, Python or related language (experience)
- - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing (experience)
Preferred Qualifications
- - Experience using Unix/Linux (experience)
- - Experience in professional software development (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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. (experience)
Responsibilities
- - You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence
- - You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases
- - Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints
- - Create, innovate, and deliver deep learning, policy-based learning, and/or machine learning-based algorithms to deliver customer-impacting results
- - Perform model/data analysis and monitor metrics through online A/B testing