Applied Scientist, Customer360
Amazon•Published 23 hours ago•First seen 3 hours ago
What happens when you give AI the ability to remember? Not cached responses — real structured memory that compounds over time and transfers across contexts. We're building the science behind this, and we need researchers who want to own the problem end-to-end. This is a founding role on a new team. You won't inherit models or maintain someone else's pipeline. You'll define the research direction, run experiments at scale, and ship what works directly to production.
Key job responsibilities
As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for knowledge acquisition and retrieval. You will adopt or invent new machine learning and analytical techniques in the realm of information retrieval, knowledge representation, and large language models. Specific responsibilities include:
1. Design and implement novel approaches to knowledge extraction from heterogeneous, unstructured data sources at organizational scale.
2. Build retrieval systems that match intent to relevant knowledge across domains — solving the "right memory at the right time" problem.
3. Own the quality of memory generation: what to capture, how to structure it, when to surface it, and when to let it decay.
4. Run large-scale experiments using Amazon's compute infrastructure and massive real-world datasets.
5. Develop evaluation frameworks for a system where "quality" means something new — right knowledge, right context, right confidence level.
6. Collaborate with engineers to move from research prototype to production system in weeks, not quarters.
7. Invent new approaches to temporal knowledge management — how memories age, conflict, and compound over time.
8. Publish and patent novel approaches to knowledge acquisition and retrieval at top-tier venues.
A day in the life
You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, execute experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the organization. You get to influence stakeholders with clear communication skills. You innovate on behalf of the customer and strategically build features. You will mentor junior members and help them grow.
About the team
We're a new team within Personalization, focused on a different kind of recommendation: not "what product should this customer see" but "what knowledge should this AI use right now." Same scale, same rigor, entirely new problem space. The science is at the intersection of information retrieval, knowledge representation, and LLM reasoning — and the right approach hasn't been established yet.
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.
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.
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually
Key job responsibilities
As an Applied Scientist in our team, you will be responsible for the research, design, and development of new AI technologies for knowledge acquisition and retrieval. You will adopt or invent new machine learning and analytical techniques in the realm of information retrieval, knowledge representation, and large language models. Specific responsibilities include:
1. Design and implement novel approaches to knowledge extraction from heterogeneous, unstructured data sources at organizational scale.
2. Build retrieval systems that match intent to relevant knowledge across domains — solving the "right memory at the right time" problem.
3. Own the quality of memory generation: what to capture, how to structure it, when to surface it, and when to let it decay.
4. Run large-scale experiments using Amazon's compute infrastructure and massive real-world datasets.
5. Develop evaluation frameworks for a system where "quality" means something new — right knowledge, right context, right confidence level.
6. Collaborate with engineers to move from research prototype to production system in weeks, not quarters.
7. Invent new approaches to temporal knowledge management — how memories age, conflict, and compound over time.
8. Publish and patent novel approaches to knowledge acquisition and retrieval at top-tier venues.
A day in the life
You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, execute experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the organization. You get to influence stakeholders with clear communication skills. You innovate on behalf of the customer and strategically build features. You will mentor junior members and help them grow.
About the team
We're a new team within Personalization, focused on a different kind of recommendation: not "what product should this customer see" but "what knowledge should this AI use right now." Same scale, same rigor, entirely new problem space. The science is at the intersection of information retrieval, knowledge representation, and LLM reasoning — and the right approach hasn't been established yet.
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
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience in designing experiments and statistical analysis of results
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
Preferred Qualifications
- Experience using Unix/Linux
- Experience in professional software development
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