Principal AI Scientist, Knowledge & Retrieval Systems

Amazon Inc.; Seattle (WA); On-site; USD 199,000 - 269,000; Full time

Benefits offered by this job

Health insurance

RSUs and comprehensive benefits

401(k) matching

Job summary

Amazon Inc. in Seattle, WA, seeks a Principal Applied Scientist to own the scientific direction of AWS Applied AI Solutions (AAIS).

You will lead a team of applied scientists and MLEs, prototype ideas in production data, and shape the strategy across knowledge representation, temporal reasoning, retrieval, and evaluation. The role emphasizes building synthetic data pipelines, defining proactive AI behavior, and driving a strong learning loop from human feedback to production.

Qualifications

• PhD in Computer Science, ML, Statistics or MS with 8+ years of applied science experience
• 10+ years building and shipping machine learning or AI systems that reached production
• Deep expertise in large language models and at least two of: information retrieval, knowledge representation and graphs, reinforcement learning, agentic system design, or evaluation methodology for generative systems
• Demonstrated experience setting technical and scientific direction for a team of scientists, including mentoring senior scientists
• Hands-on proficiency in Python and the ability to prototype independently in a production codebase
• Track record of publications, patents, or equivalent evidence of original scientific contribution

Responsibilities

• Own the scientific strategy for how organizational knowledge is represented, kept current, and retrieved: extraction, entity resolution, deduplication, graph structure, and retrieval that unifies graph, semantic, keyword, and temporal search.
• Advance temporal reasoning. Representing what superseded what and when, and preserving provenance to distinguish confirmed information from inferred information.
• Define the science of proactive behavior. Determine when an AI system should interrupt a human, with precision-critical thresholds.
• Lead our measurement science for a multi-component agentic system, converging on primary metrics.
• Build synthetic and simulated data pipelines to create controlled, realistic scenarios for development and testing.
• Own the learning loop by turning human interaction into training signal for near-term and long-term improvements.
• Make frontier-model vs domain-tuned-model cost/need decisions with data-driven justification.
• Mentor scientists, review designs, publish where appropriate, and represent science externally.

Job description

Amazon Inc. in Seattle, WA, seeks a Principal Applied Scientist to own the scientific direction of AWS Applied AI Solutions (AAIS).

You will lead a team of applied scientists and MLEs, prototype ideas in production data, and shape the strategy across knowledge representation, temporal reasoning, retrieval, and evaluation. The role emphasizes building synthetic data pipelines, defining proactive AI behavior, and driving a strong learning loop from human feedback to production.