Senior Applied Scientist, Personalization & Knowledge Systems

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

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon Science is seeking a Senior Applied Scientist to define the scientific roadmap for a new AI memory system. You will own the research agenda, run experiments toward deployment targets, and mentor junior scientists.

The team is forming now, with autonomy to shape the direction from day one. You will lead end-to-end research from problem formulation through production impact, partner with engineering to translate research into architecture decisions, and publish work at top venues to advance

Qualifications

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

Responsibilities

• Define the scientific roadmap for knowledge acquisition, representation, and retrieval at scale.
• Lead research on how AI systems should learn from experience and generalize.
• Design evaluation frameworks for systems with new quality metrics.
• Own end-to-end research from problem formulation to production impact.
• Mentor Applied Scientists and set scientific standards.
• Collaborate with engineering leadership to translate research into architecture.
• Drive model architecture decisions, training methods, and evaluation.
• Publish at top-tier venues and advance applied knowledge systems.

Skills

Applied research

ML models for business

Programming: Java/C++/Python

Neural networks / deep learning

System design for ML

Education

PhD or Master's + 6+ years research

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

numpy

scipy

Hadoop

Spark

Job description

Amazon Science is seeking a Senior Applied Scientist to define the scientific roadmap for a new AI memory system. You will own the research agenda, run experiments toward deployment targets, and mentor junior scientists.

The team is forming now, with autonomy to shape the direction from day one. You will lead end-to-end research from problem formulation through production impact, partner with engineering to translate research into architecture decisions, and publish work at top venues to advance