Senior Applied Scientist, Neuro-Symbolic AI Labs (AWS)

Amazon; Boston (MA); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking a Senior Applied Scientist for the Neuro-Symbolic AI Labs in Boston to lead research that leverages proof assistants to guide learning and reasoning. You will shape the definition, vision, and development of product features from start to finish.

Responsibilities include designing neuro-symbolic applications, thriving in an agile environment, and delivering high-quality scientific artifacts. Eligibility includes PhD or equivalent experience and strong ML, Java/C++/Python skills.

Qualifications

• 3+ years of building ML models for business application experience.
• PhD, or Master's degree and 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Define and implement new neuro-symbolic applications that employ scalable and efficient approaches to solve complex problems.
• Work in an agile, startup-like development environment, where you are always working on the most important stuff.
• Deliver high-quality scientific artifacts.

Skills

Java

C++

Python

Deep learning

ML models

Education

PhD or Master's + 6+ yrs applied research

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

numpy

scipy

Job description

Senior Applied Scientist, Neuro-Symbolic AI Labs

Job ID: 10503196 | Amazon Development Center U.S., Inc.

We are looking for researchers who aim to build super-intelligent AI systems that leverage proof assistants to guide learning and reasoning. Our neuro-symbolic AI technology is applied across a wide range of science and engineering domains within Amazon, and you will join the team at the forefront of this research.

As a Senior Applied Scientist, you will play a pivotal role in shaping the definition, vision, and development of product features from beginning to end.

You will:

• Define and implement new neuro-symbolic applications that employ scalable and efficient approaches to solve complex problems.
• Work in an agile, startup-like development environment, where you are always working on the most important stuff.
• Deliver high-quality scientific artifacts.

About the team

We work closely with academia. Our team includes an Amazon Scholar in mathematics, and we maintain active research collaborations with faculty at leading CS departments (MIT, Berkeley, CMU).

Basic Qualifications

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

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 .

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.

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 (RSU). 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, MA, Boston - 167,100.00 - 226,100.00 USD annually

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https://www.amazon.jobs/en/faqs#faqs-for-us-government-employees

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.