Role at a glance
- Salary
- $167.1K – $226.1K/yr
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Education
- PhD, or Master's degree and 6+ years of applied research experience
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Role Summary
The Senior Applied Scientist will lead the research direction for an AI system focused on persistent, compounding memory. The role sits within a team applying large-scale machine learning to knowledge acquisition, representation, retrieval, and reasoning, with research tied to production impact.
What You'll Do
- Define the scientific roadmap for knowledge acquisition, representation, and retrieval at organizational scale.
- Lead research on how AI systems should learn from experience, including what to capture, how to generalize, and when to forget.
- Design evaluation frameworks for system quality based on the right knowledge, context, and confidence level.
- Own end-to-end research from problem formulation through production impact measurement.
- Mentor Applied Scientists and establish scientific standards for a new team.
- Partner with engineering leadership to translate research into architecture decisions that shape the product.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required
- 4+ years of applied research experience
- 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
- 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.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Key job responsibilities
As a Senior Applied Scientist, you will own the scientific roadmap for personalization initiatives, identifying high-impact research directions and translating ambiguous problems into well-defined ML formulations. You will lead end-to-end systems spanning knowledge acquisition, retrieval, and reasoning. Specific responsibilities include:
1. Define the scientific roadmap for knowledge acquisition, representation, and retrieval at organizational scale.
2. Lead research on how AI systems should learn from experience — what to capture, how to generalize, when to forget.
3. Design evaluation frameworks for a system where "quality" means something new — right knowledge, right context, right confidence level.
4. Own end-to-end research from problem formulation through production impact measurement.
5. Mentor Applied Scientists and establish scientific standards for a new team.
6. Partner with engineering leadership to translate research into architecture decisions that shape the product.
7. Drive technical decisions on model architecture, training methodology, and evaluation frameworks, balancing scientific rigor with business impact.
8. Publish at top-tier venues and advance the state of the art in applied knowledge systems.
About the team
Born out of Amazon's Personalization organization, which pioneered personalization at internet scale. We're applying deep expertise in large-scale ML to a fundamentally new domain where the signal space, objective functions, and evaluation criteria are all open research questions.
The team values innovation and offers a safe place to try, fail, and learn while fostering a culture of continuous improvement. Everyone is a leader and owner for everything we do as a team. We offer creative space with an entrepreneurial work environment focusing on customer obsession.
Basic Qualifications
- 4+ years of applied research experience- 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.
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.