Applied Scientist: Computer Vision for Workplace Safety

Amazon; Nashville (TN); On-site; USD 136,000 - 184,000; Full time

Job summary

Amazon is hiring an Applied Scientist to build computer vision and ML models to enhance workplace safety for over 1.5 million employees globally. The role focuses on activity recognition, anomaly detection, object detection, and risk prediction using video, image, and sensor data from Amazon's operations.

You'll work with engineers to move models from experiments to production at scale, translating research into measurable safety outcomes across hundreds of facilities.

Qualifications

• PhD or Master’s degree plus 4+ years of CS, CE, ML or related field experience.
• 3+ years of building models for business applications.
• Experience in patents or publications at top-tier conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms, data structures, numerical optimization, data mining, parallel and distributed computing, HPC.

Responsibilities

• Design, develop, and deploy CV and ML models for workplace safety applications.
• Develop and iterate on model architectures using deep learning on large-scale datasets.
• Collaborate with software engineers to productionize models with optimized latency and reliability.
• Analyze operational data to identify safety risks and improve models.
• Stay current with CV and ML research and assess applicability to safety use cases.
• Communicate findings clearly to technical and non-technical stakeholders.

Skills

Java

C++

Python

Algorithms

Data mining

Distributed computing

High-performance computing

Unix/Linux

Education

PhD

Master's in CS/CE/ML

Tools

Unix/Linux

Job description

Amazon is hiring an Applied Scientist to build computer vision and ML models to enhance workplace safety for over 1.5 million employees globally. The role focuses on activity recognition, anomaly detection, object detection, and risk prediction using video, image, and sensor data from Amazon's operations.

You'll work with engineers to move models from experiments to production at scale, translating research into measurable safety outcomes across hundreds of facilities.