Principal Scientist, AI Agents & WorkSpaces

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

Job summary

Amazon Science seeks a Principal Applied Scientist to own the scientific vision across Agentic WorkSpaces, shaping the research roadmap for Personal, Applications, and Core surfaces. You will define benchmarks, performance metrics, and the science agenda for agentic systems and human-AI teamwork.

You will lead cross-organizational efforts with VP-level buy-in, drive experimentation rigor, and contribute to external publications and open-source projects.

Qualifications

• PhD in Computer Science, ML or related field or Master's with applied research experience.
• 10+ years of applied science experience, including 8+ years applying ML to real-world products at scale.
• Experience setting research direction and technical strategy across multiple teams.

Responsibilities

• Set the long-term scientific vision and multi-year research roadmap for Agentic WorkSpaces.
• Solve highly ambiguous, novel problems in agent perception, reasoning, evaluation, and human-AI collaboration.
• Own the evaluation and measurement foundation with benchmarks, datasets and metrics.
• Drive cross-organizational scientific alignment across partner teams and product portfolio.
• Deliver measurable business impact through improved accuracy, cost efficiency, and productivity.
• Raise the scientific bar through rigorous experimentation and mentorship of staff.
• Advance state-of-the-art via publications, patents, and open-source contributions.

Skills

Research leadership

Direction setting

LLMs/foundation models

Experiment design

Cross-team collaboration

Education

PhD in Computer Science, ML or related

Master's with applied research experience

Tools

Python

ML frameworks

Experiment tracking

Job description

Amazon Science seeks a Principal Applied Scientist to own the scientific vision across Agentic WorkSpaces, shaping the research roadmap for Personal, Applications, and Core surfaces. You will define benchmarks, performance metrics, and the science agenda for agentic systems and human-AI teamwork.

You will lead cross-organizational efforts with VP-level buy-in, drive experimentation rigor, and contribute to external publications and open-source projects.