Senior ML Scientist — Shopping Catalog Innovation

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

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon Science in Seattle seeks a Senior Applied Scientist to lead AI/ML innovation for expanding Amazon's product catalogue. You will design and deploy state-of-the-art models, run rigorous experiments, and translate breakthroughs into production-ready solutions while guiding junior scientists.

You will collaborate with ML Engineers and Software Development Engineers to optimize performance, ensure scalability, and deploy low-latency solutions at Amazon scale in a global setting.

Qualifications

• 3+ years building ML models for business applications.
• PhD or MS with 6+ years of applied research experience.
• Experience programming in Java, C++, Python.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Lead research and development of novel ML approaches for catalogue expansion.
• Design and develop state-of-the-art ML models and conduct rigorous experiments.
• Translate breakthroughs into production-ready solutions and production deployment.
• Guide a team of junior scientists and collaborate with ML Engineers and SDEs.
• Optimize model performance for scalability and low-latency Amazon-scale systems.

Skills

Machine learning

Java / C++ / Python

Deep learning

Education

PhD, or MS + 6+ years applied research

Tools

TensorFlow

scikit-learn

Spark MLLib

MxNet

NumPy

Job description

Amazon Science in Seattle seeks a Senior Applied Scientist to lead AI/ML innovation for expanding Amazon's product catalogue. You will design and deploy state-of-the-art models, run rigorous experiments, and translate breakthroughs into production-ready solutions while guiding junior scientists.

You will collaborate with ML Engineers and Software Development Engineers to optimize performance, ensure scalability, and deploy low-latency solutions at Amazon scale in a global setting.