Sr. Applied Scientist, C360

Amazon Science; Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Job summary

Amazon Science in Seattle, WA seeks a senior scientist to define and own the research roadmap for a system with persistent, compounding memory. This role draws from recommendations, search and summarization while defining the field’s direction.

You’ll own the scientific roadmap, run a research agenda with real-world deployment targets, and mentor junior scientists. You will lead end-to-end research from problem formulation through production impact, translating findings into architectural

Qualifications

• 3+ years of building ML models for business applications
• PhD or Master’s with 6+ years of applied research experience
• Proficiency in Java, C++, Python or related languages
• Experience with neural deep learning methods and ML

Responsibilities

• Define the scientific roadmap for knowledge acquisition, representation, and retrieval at organizational scale.
• Lead research on how AI systems should learn from experience — what to capture, how to generalize, when to forget.
• Design evaluation frameworks for a system where quality means right knowledge, context, and confidence.
• 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.
• Drive technical decisions on model architecture, training methodology, and evaluation frameworks.
• Publish at top-tier venues and advance the state of the art in applied knowledge systems.

Skills

Machine learning

Research leadership

Programming (Java, C++, Python)

Deep learning

Education

PhD

Masters + 6+ years applied research

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Hadoop

Spark

Job description

Description

We're looking for a senior scientist to lead the research direction for a system that gives AI persistent, compounding memory. This is a new problem space — not recommendation, not search, not summarization, though it draws from all three. The right scientist will define what this field becomes. You'll own the scientific roadmap, run a research agenda with real-world deployment targets, and mentor junior scientists. The team is forming now. Your first week will involve scoping experiments, not reading onboarding docs.

We're looking for a senior scientist to lead the research direction for a system that gives AI persistent, compounding memory. This is a new problem space — not recommendation, not search, not summarization, though it draws from all three. The right scientist will define what this field becomes. You'll own the scientific roadmap, run a research agenda with real-world deployment targets, and mentor junior scientists. The team is forming now. Your first week will involve scoping experiments, not reading onboarding docs.

Responsibilities

• Define the scientific roadmap for knowledge acquisition, representation, and retrieval at organizational scale.
• Lead research on how AI systems should learn from experience — what to capture, how to generalize, when to forget.
• Design evaluation frameworks for a system where "quality" means something new — right knowledge, right context, right 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.
• Drive technical decisions on model architecture, training methodology, and evaluation frameworks, balancing scientific rigor with business impact.
• Publish at top-tier venues and advance the state of the art in applied knowledge systems.

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

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

• 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