招聘
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 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 electronic devices.
AE team is looking for a 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.
Basic Qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of designing experiments and statistical analysis of results experience
- Experience programming in Java, C++, Python or related language
- Knowledge of standard speech and machine learning techniques
Preferred Qualifications
- Experience in designing experiments and statistical analysis of results
- Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS
- Experience applying theoretical models in an applied environment
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
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About Amazon

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
Employees
Seattle
Headquarters
Reviews
2.9
10 reviews
Work Life Balance
2.8
Compensation
3.7
Culture
2.5
Career
2.3
Management
2.1
35%
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Pros
Good pay and compensation
Strong benefits package
Flexible scheduling options
Cons
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
Salary Ranges
2 data points
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L4
0 reports
$181,968
total / year
Base
-
Stock
-
Bonus
-
$154,672
$209,264
Interview Experience
10 interviews
Difficulty
3.7
/ 5
Duration
21-35 weeks
Offer Rate
20%
Experience
Positive 10%
Neutral 10%
Negative 80%
Interview Process
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
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