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Software Development Manager - Computer Vision

Software Development Manager - Computer Vision

Job ID 
Posted Date 
Amazon Web Services, Inc.
Position Category 
Software Development
Recruiting Team 

Job Description

Are you interested in shaping the future of computer vision ? Do you want to define the next generation Artificial Intelligence that will understand what is in a picture or a video ? Amazon Rekognition Service allows any developer to create applications that leverage our technology. We are growing quickly and we need your passion, innovative ideas, and creativity to help continue to deliver on our ambitious goals.
Amazon Rekognition is a service that makes it easy to add image analysis to your applications. With Rekognition, you can detect objects, scenes, and faces in images. You can also search and compare faces. Rekognition’s API enables you to quickly add sophisticated deep learning-based visual search and image classification to your applications.
We have an ambitious charter, and on this team you’ll be able to get your hands on lots of technologies. Above all, you’ll be leading the design and implementation of new scalable services. These back-end services are areas we are investing in as we continue to grow at scale, processing large amounts of data to make sure Amazon customers discover content they care about. You'll get to build on top of Amazon’s vast development infrastructure, including AWS as well as internal tools for setting up continuous deployment and real-time monitoring.
We are seeking a software development manager that is a technology leader and demonstrates exemplary practice leading teams of engineers in the design and implementation of new scalable computer vision services. He/she will lead technology areas that drive solutions for a super solid, scalable, efficient, and extremely fault tolerant service. The individual should also be a thought leader in influencing our overall strategy by helping define the product features, driving system architecture, and spearheading the best practices that enable a quality product. The ideal candidate will be passionate about solving some of the hardest engineering challenges in distributed systems at massive scale and computer vision on an ongoing basis and have a demonstrable track record for delivering successful products and leading highly effective teams. Prior experience with computer vision or image processing systems will be a significant plus.

This hands-on position requires broad engineering competence and in-depth technical knowledge of service engineering, as well as demonstrated experience successfully planning, organizing, and leading software development projects in a dynamic environment.

This position within the Rekognition team presents a unique and rare opportunity to get in on the ground floor within a fast growing business and help shape the technology, product and the business. A successful candidate will bring deep technical and software expertise, strong business acumen and judgment, an ability to define visionary, ground breaking products, desire to have an industry wide impact and ability to work within a fast moving, startup environment in a large company to rapidly deliver services that have a broad business impact.

Basic Qualifications

  • Master's/Bachelor's Degree in Computer Science
  • Proven skills designing and developing simple solutions to complex, customer challenges.
  • 7+ years experience developing software
  • 3+ years experience managing software development teams
  • Experience leading and developing highly-skilled software engineering teams
  • Experience forming teams and recruiting software engineers
  • Good understanding of various platforms and technologies (AWS, Java, Python)
  • Excellent written and verbal communication skills

Preferred Qualifications

  • Experience in machine learning and/or image processing
  • Strong business and technical vision
  • Deep hands-on technical expertise

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation