Applied Scientist, PXT Central Science

Amazon
San Francisco, CA, USA / Boston, MA, USA / Arlington, VA, USA2026-08-27ONSITE

About the job

We are seeking an Applied Scientist to build production machine learning systems that solve complex business problems at scale. You will design, develop, and deploy ML solutions that directly impact millions of users and drive strategic decision-making across the organization.

In this role, you will work on challenging problems spanning predictive modeling, natural language processing, recommendation systems, and generative AI applications. You will collaborate with cross-functional teams to translate ambiguous business challenges into rigorous technical solutions.

Responsibilities

Design and deploy large-scale machine learning systems in production environments

Develop innovative ML solutions using state-of-the-art techniques including deep learning, NLP, and generative AI

Create ML solutions that personalize manager on-boarding and development experiences — identifying individual capability gaps, recommending tailored learning pathways, and measuring development effectiveness across diverse manager populations and contexts

Partner to build causal inference models and experimental frameworks to measure impact

Collaborate with product managers, engineers, and business leaders to define technical roadmaps

Communicate complex technical concepts to diverse audiences, from technical peers to senior leadership

Qualifications

Minimum

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 in patents or publications at top-tier peer-reviewed conferences or journals

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

Preferred

Experience using Unix/Linux

Experience in professional software development