Senior Applied Scientist, Edge Vision & Robotics

Amazon Inc.; Reading (MA); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

Paid time off

401(k) Plan

Job summary

Amazon Robotics seeks a Senior Applied Scientist to advance computer vision and ML for robotic sensing hardware. The role blends ML research with hardware, guiding sensor selection, compute architectures, and edge inference on real robots across fulfillment centers.

You will co-develop production-grade perception systems, publish research, mentor engineers, and push the state of the art while ensuring practical deployment and reliability at scale.

Qualifications

• PhD or Master’s degree with 6+ years of applied research experience.
• Experience programming in Java, C++, Python.
• Proven ability to deliver complex DL/vision systems to customers.
• Experience with PyTorch, TensorFlow, or equivalent.
• Experience with 2D/3D vision tasks and edge deployment.
• Strong written and verbal communication for executives.

Responsibilities

• Co-define sensing and compute hardware requirements with senior engineers.
• Develop and optimize computer vision and DL models for robotic perception for edge deployment.
• Lead ML experimentation and validation influencing hardware architecture.
• Design benchmarking frameworks for sensing hardware performance.
• Collaborate with hardware, software, and robotics teams to transition prototypes to production.

Skills

Java

C++

Python

Deep learning

Computer vision

Edge deployment

Communication

Education

PhD

Master's degree

Tools

PyTorch

TensorFlow

OpenCV

CUDA

Job description

Amazon Robotics seeks a Senior Applied Scientist to advance computer vision and ML for robotic sensing hardware. The role blends ML research with hardware, guiding sensor selection, compute architectures, and edge inference on real robots across fulfillment centers.

You will co-develop production-grade perception systems, publish research, mentor engineers, and push the state of the art while ensuring practical deployment and reliability at scale.