Senior Applied Scientist, Robotics AI & Continuous Learning

Amazon; Massachusetts; On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Industrial Robotics is seeking an Applied Scientist III to develop and deploy machine learning systems that enable robots to learn from fleet experience and continuously improve performance. You will collaborate with robotics teams, software engineering, and operations to power intelligent systems at scale.

You will write major portions of critical code, research new algorithms, and contribute to roadmaps while delivering robust, production-ready solutions for real-world robotic

Qualifications

• PhD in a quantitative field or Master’s with 12+ years ML production experience.
• 5+ years applying ML to solve complex problems in real-world systems.
• Strong programming experience in Java, C++, or Python.

Responsibilities

• Identify and devise new scientific approaches for continuous learning and fleet optimization.
• Lead design and delivery of complex ML solutions for production environments.
• Design and build ML models including reinforcement learning infrastructure and anomaly detection.
• Write significant scientific code with scalable, maintainable implementations.
• Conduct rapid experiments with reproducible results, bridging simulation and real-world robotics.

Skills

Java

C++

Python

Machine learning

NLP

Publications patents

Education

PhD in engineering / CS / ML / robotics

Master's + 12+ years ML production experience

Tools

TensorFlow

Spark MLlib

Hadoop

ElasticSearch

Job description

Amazon Industrial Robotics is seeking an Applied Scientist III to develop and deploy machine learning systems that enable robots to learn from fleet experience and continuously improve performance. You will collaborate with robotics teams, software engineering, and operations to power intelligent systems at scale.

You will write major portions of critical code, research new algorithms, and contribute to roadmaps while delivering robust, production-ready solutions for real-world robotic