Applied Scientist

DESCRIPTION

Job summary
The Team: Amazon Go is a new kind of store with no lines and no checkoutyou just grab and go! Customers simply use the Amazon Go app to enter the store, take what they want from our selection of fresh, delicious meals and grocery essentials, and go!

Our checkout-free shopping experience is made possible by our Just Walk Out Technology, which automatically detects when products are taken from or returned to the shelves and keeps track of them in a virtual cart. When you’re done shopping, you can just leave the store. Shortly after, we’ll charge your Amazon account and send you a receipt. Check it out at amazon.com/go. Designed and custom-built by Amazonians, our Just Walk Out Technology uses a variety of technologies including computer vision, sensor fusion, and advanced machine learning. Innovation is part of our DNA! Our goal is to be Earths’ most customer centric company and we are just getting started. We need people who want to join an ambitious program that continues to push the state of the art in computer vision, machine learning, distributed systems and hardware design.

The Role: 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. We’ll need to tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems.
As an Applied Scientist, you will help solve a variety of technical challenges and mentor other scientists and engineers. Given that this is an early-stage initiative, you will play an active role in translating business and functional requirements into concrete deliverables and build quick prototypes or proofs of concept in partnership with other technology leaders within the team. You will tackle challenging, novel situations every day and given the size of this initiative, you’ll have the opportunity to work with multiple technical teams across Amazon. You should be comfortable with a degree of ambiguity that’s higher than most projects and relish the idea of solving problems that, haven’t been solved at scale before – anywhere. Along the way, we guarantee that you’ll learn a ton, have fun and make a positive impact on millions of people.

BASIC QUALIFICATIONS

• MS in Computer Science, strong knowledge of machine learning, and 5+ years of relevant experience in industry and/or academia OR PhD in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related quantitative field and strong knowledge of machine learning.
• 2 +/- years of experience using a broad set of supervised and unsupervised ML approaches and techniques ranging from Regression to Deep Neural Networks.
• Proven track record of successfully applying ML-based solutions to complex problems in business, science, or engineering.
• Ability to develop practical solutions to complex problems
• Strong communication and collaboration skills
• Proficiency in C/C++, python, and/or java

PREFERRED QUALIFICATIONS

• PhD in Computer Science or Machine Learning, AI, Statistics, Electrical Engineering or equivalent;
• More than 4 years of industrial/academic experience in building classification models
• Ability to handle multiple competing priorities in a fast-paced environment
• Significant peer reviewed scientific contributions in premier journals and conferences
• Strong personal interest in learning, researching, and creating new technologies with high customer impact
• Experience with defining research and development practices in an applied environment;
• Proven track record in technically leading and mentoring scientists;
• Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
• Strong fundamentals in problem solving, algorithm design and complexity analysis

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.