Applied Scientist Intern, Amazon Lab126, Taiwan Full-time

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, and Amazon Echo. What will you help us create?

Key job responsibilities

You will be working on developing Computer Vision algorithms to improve deep learning models including reducing the sample complexity, improving generalization ability, boosting model robustness, etc. You will be a critical science contributor and can create a significant business impact to the company. This opportunity requires excellent technical, problem-solving, and communication skills. An ideal candidate will have a high teamwork mentality coupled with a strong bias for action yet always insisting on the highest standards. We also aim to publish our innovation and findings to computer vision top conferences including CVPR, ICCV, ECCV.

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A day in the life

In this role, you will work closely with other researchers in the team to research, design, and deliver science components powering computer vision and active learning algorithms to cost-effectively create very large-scale training datasets for various computer vision/robotics applications. You will have the unique opportunity to work on multiple popular Computer Vision tasks altogether, therefore, embrace the great potential to innovate more.

About the team

We are a smart team of doers that work passionately to apply cutting-edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. The team is using computer vision, machine learning, sensor fusion, real-time and distributed systems to convert requirements into concrete deliverables. A Researcher on this team will translate business and functional requirements into working code. Comfort with a high degree of ambiguity and ability to solve problems that haven’t been solved to scale before are essential.

BASIC QUALIFICATIONS

– Bachelor’s degree in computer science, electrical engineering, or related field

PREFERRED QUALIFICATIONS

– Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS

– Experience programming in Java, C++, Python or related language

– Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning

– Experience applying theoretical models in an applied environment

– Experience in investigating, designing, prototyping, and delivering new and innovative system solutions

– Master’s or PhD degree in computer science, electrical engineering, or related field