Principal Applied Scientist

Job description

DESCRIPTION

The Team: How often have you had an opportunity to be a founding member of a team that is tasked with solving a huge business problem through innovative technology? Would you like to know more about how computer vision and machine learning can be used to solve these problems? If this sounds intriguing, then we'd like to talk to you about a role on a new Amazon team that's tackling a set of problems requiring significant innovation.

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 a Sr. Research Scientist, you will help tackle a variety of technical challenges. 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 should be comfortable with a degree of ambiguity that's higher than most projects and relish the idea of solving problems that, frankly, haven't been solved at scale before - anywhere. 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 at Amazon in different locations. Along the way, we guarantee that you'll learn a ton, have fun and make a positive impact on millions of people.

Desired profile

BASIC QUALIFICATIONS

· Master's/PhD in Computer Science or related field
· Fluency in one or more of: Java, C, C++; and familiarity with one or more of: Python, Perl, PHP.
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· Understanding of Software Development Life Cycle (SDLC) and project planning/execution skills including estimating and scheduling.
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· Academic and/or industry experience with one of more of the following domains: computer vision, image recognition, machine learning or distributed systems.