Applied Scientist

Job ID: 1660402 | Amazon.com Services LLC

DESCRIPTION

Come join Amazon Halo's Computer Vision and Machine Learning Science team!

We are looking for an Applied Scientist passionate about improving customers’ health and wellness to join our growing CVML science team.

As an Applied Scientist, you will be a member of an algorithm team responsible for the end-end delivery of CVML-based algorithms.

Job responsibilities
· Research, develop, implement and evaluate novel CVML algorithms
· Work on large-scale datasets, focusing on creating scalable and accurate CVML systems in versatile application fields
· Design data collection experiments, perform statistical analysis and deliver ML models.
· Collaborate closely with team members on developing systems from prototyping to production level
· 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


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.

BASIC QUALIFICATIONS

· MS in Computer Vision, Machine Learning, or related field
· 3+ years of experience in implementing algorithms in computer vision or machine learning using both toolkits and self developed code
· 1+ years of experience in Java, C++, or other programming language, as well as with Python or similar scripting language
· Ability to develop experimental and analytic plans for data modeling processes

PREFERRED QUALIFICATIONS

· PhD in Computer Vision, Machine Learning, or related field
· 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
· Depth and breadth in state-of-the-art computer vision and machine learning technologies