Computer Vision and Remote Sensing Data Scientist

US, VA, Virtual Location - Virginia

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Job summary
The Amazon Web Services (AWS) Public Sector Professional Services team is looking for a passionate and talented Data Scientist who will collaborate with other scientists and engineers to develop computer vision capabilities to address customer use-cases at enterprise scale. If you are excited to work with massive amounts of data and computer vision models to solve real world challenges, this is the position for you! We work directly with public sector entities, medical centers, and non-profits to achieve their mission goals through the adoption of Machine Learning (ML) methods. We apply computer vision to numerous imagery and sensor types, such as satellite imagery, medical imaging, aerial video, and more! Amazon has been investing in Machine Learning for decades, and by joining AWS you’ll join a community of scientists and engineers developing leading edge solutions for enterprise-scale data science applications.

In this position, you will guide teams in architecting and implementing innovative, AWS Cloud-native ML solutions, providing direct and immediate impact for your customers. You will take the lead in planning, designing, and running experiments, researching new algorithms, and will work closely with talented data scientists and engineers to put your algorithms and models into practice to help solve our customers' most challenging problems. You will also guide teams in the development of new solutions and aid customers in adopting AWS ML capabilities.

The AWS Professional Services Public Sector Data & ML team is primarily virtual, though employees are welcome to work on-site at any AWS Corporate office. Employees can live anywhere in the United States.

This position involves up to 25% travel.

In this role, you will:

* Engage directly with customers to understand the business problems and aid them in implementing their ML solutions.
* Deliver Machine Learning projects from beginning to end. This includes understanding the business need, planning the project, aggregating & exploring data, building & validating predictive models, and deploying completed ML capabilities on the AWS Cloud to deliver business impact for the customer.
* Use Deep Learning frameworks like PyTorch, Tensorflow and MxNet to help our customers build computer vision models.
* Work on large-scale datasets, creating scalable, robust and accurate computer vision systems in versatile application fields.
* Work with our Professional Services Machine Learning Engineers to help our customers operationalize ML capabilities you develop.
* Collaborate with Cloud Architects to build secure, robust, and easy-to-deploy machine learning solutions.
* Research, implement, and evaluate novel computer vision algorithms.
* Work closely with customer account teams, scientific research teams and product engineering teams to optimize model implementations and deploy cutting-edge internal algorithms for your customers.
* Assist customers with Machine Learning Operations (MLOps) workflows such as model deployment, retraining, testing, and performance monitoring.

This position requires that the candidate selected be a US Citizen and hold or be able to acquire an active security clearance.

Basic Qualifications


* BS degree with 5+ years of experience, or a MS degree and 2+ years of professional experience, or a Doctorate Degree in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
* 2+ years professional experience with scientific programming languages like Python or R
* 2+ years of industry experience in data science
* A track record of building computer vision models
* 5+ years of experience diving into data to discover hidden patterns

Preferred Qualifications

* AWS Certifications, for example AWS Solution Architect Associate/Professional, ML Specialty, or Developer Associate
* Experience working with satellite imagery, aerial imagery, medical imagery, infrared imagery, or another “unusual” imagery data type
* Hands-on experience with state-of-the-art object detection approaches
* 1+ years of experience with AWS services like SageMaker, S3, EC2, and Rekognition
* Experience with distributed training (e.g., DDP, Horovod) and model compilation (e.g., TensorRT, TVM, or SageMaker Neo) frameworks
* A track record of training production-ready neural networks
* 2+ years of experience handling terabyte-scale datasets
* Experience deploying computer vision models, specifically neural networks, into production environments
* Experience designing and deploying cloud-native, enterprise-scale machine learning solutions in the AWS Cloud or with another major cloud provider
* Experience developing automation to solve problems at scale
* Strong communication skills
#US_WWPS_ProServ #US_WWPS_ProServ_DML

The pay range for this position in Colorado is $140,000 - 180,000 (yr.); however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site.


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.

Tags: AWS Computer Vision DDP Deep Learning EC2 Economics Engineering Horovod Machine Learning Mathematics MLOps Model deployment MXNet Python PyTorch R Research SageMaker Security Statistics TensorFlow TensorRT Testing

Perks/benefits: Career development Signing bonus

Regions: Remote/Anywhere Africa North America
Country: United States
Job stats:  51  7  0

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