Applied Scientist: Computer Vision for Transportation

Amazon; Factoria (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking an Applied Scientist for Amazon Transportation Services in Bellevue, WA. You will develop, train, and productionize computer vision models across a portfolio of high-impact use cases, turning visual data into automated operational decisions.

You will work with scientists, business owners, and engineers to validate approaches, design experiments, and launch models to production. This is a hands-on role with broad scope and measurable impact.

Qualifications

• 3+ years of building machine learning models for business application experience.
• PhD, or Master's degree with 4+ years in CS/CE/ML or related field.
• Experience developing deep learning algorithms for computer vision.
• Proficiency programming in Java, C++, Python or related language.

Responsibilities

• Develop and apply visual perception and representation learning across image and video domains.
• Own large-scale model training, fine-tuning, and learning from diverse data.
• Address real-world CV challenges like unlabeled data and varying conditions.
• Collaborate with product, operations, and engineering to define CV objectives.
• Design evaluation frameworks with precision/recall tradeoffs and costs.
• Build and maintain training and inference pipelines for production deployment.

Skills

ML model development

Deep learning

Computer vision

Software development

Education

PhD or Master's +4 yrs CS/ML

Tools

Java

C++

Python

Job description

Amazon is seeking an Applied Scientist for Amazon Transportation Services in Bellevue, WA. You will develop, train, and productionize computer vision models across a portfolio of high-impact use cases, turning visual data into automated operational decisions.

You will work with scientists, business owners, and engineers to validate approaches, design experiments, and launch models to production. This is a hands-on role with broad scope and measurable impact.