Sr. Applied Scientist, Amazon Personalization - Customer 360

Socket.dev; Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Job summary

Socket.dev is seeking a Senior Applied Scientist to lead the research direction for persistent, compounding memory in AI systems. You will own the scientific roadmap, run a research agenda with deployment targets, and mentor junior scientists in a forming team.

You will define the knowledge acquisition and retrieval roadmap, lead research on how systems learn from experience, and drive end-to-end research from problem framing to production impact.

Qualifications

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

Responsibilities

• Define the scientific roadmap for personalization initiatives and knowledge extraction at scale.
• Lead end-to-end research from problem formulation through production impact measurement.
• Mentor Applied Scientists and establish scientific standards for the team.
• Partner with engineering leadership to translate research into architecture decisions shaping the product.
• Drive model architecture, training methodology, and evaluation frameworks balancing rigor and business impact.
• Publish at top-tier venues and advance the state of the art in applied knowledge systems.

Skills

Applied research

Machine learning

Education

PhD

Master's + 6+ years applied research

Tools

Java

C++

Python

TensorFlow

PyTorch

Job 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.

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