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Senior Applied Scientist, Amazon Halo

Job ID: 1776730 | Amazon Dev Center (Tel Aviv)

DESCRIPTION

Job summary
Amazon Lab126 is an inventive research and development company that designs and engineers high-profile consumer electronics. Lab126 began in 2004 as a subsidiary of Amazon.com, Inc., originally creating the best-selling Kindle family of products. Since then, we have produced groundbreaking devices like Fire tablets, Fire TV, Amazon Echo and Halo.
What will you help us create?

Key job responsibilities
You will be part of a world-class Computer Vision team tasked with solving huge business problems through innovative technology and focus on product industrialization.
We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems. Everyone on the team needs to be entrepreneurial, wear many hats and work in a highly collaborative environment that’s more startup than big company.

Major responsibilities:
· Research, design, implement and evaluate novel computer vision algorithms
· Work on large-scale datasets, focusing on creating scalable and accurate computer vision systems in versatile application fields
· Collaborate closely with team members on developing systems from prototyping to production level
· Collaborate with teams spread all over the world
· Work closely with software engineering teams to drive scalable, real-time implementations
· Track general business activity and provide clear, compelling management reports on a regular basis

BASIC QUALIFICATIONS

PhD degree in Computer Vision, Machine Learning, or related field with 4 years of applied research experience.

3+ years of experience of building machine learning models for business applications.

Experience programming in Java, C++, Python or related language with emphasis on CV and ML pipelines.

PREFERRED QUALIFICATIONS

Experience working with large datasets and Deep Learning algorithms
Excellent written and verbal communication skills, ability to communicate effectively to both technical and nontechnical audiences