Computer Vision \u0026 ML Engineer, Computer Vision and Remote Sensing

The Amazon Web Services (AWS) US Federal Professional Services team is looking for a passionate and talented Computer Vision engineer who will collaborate with other scientists and engineers to develop computer vision and remote sensing 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, synthetic aperture radar, X-Ray, 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 customer facing position, you will architect and implement 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 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.

This position may involve local travel up to 25%.

This position requires that the candidate selected be a US Citizen and obtain and maintain an active TS/SCI security clearance with polygraph.

Key job responsibilities

In this role, you will:

* Engage directly with customers to understand their 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 and Tensorflow to help our customers build computer vision models.

* Work on TB scale datasets, creating scalable, robust and accurate computer vision systems in versatile application fields.

* Work with other Professional Services Data Scientists and Machine Learning Engineers to help our customers operationalize ML capabilities

* Collaborate with Cloud Architects to build secure, robust, and easy-to-deploy cloud-native machine learning solutions.

* 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.

* Experience applying best practices from core Software Development activities to Machine Learning (deployability, unit testing, well structured extensible software, etc.)

About the team

Work/Life Balance

Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentor-ship & Career Growth

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentor ship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded Evaluator and enable them to take on more complex tasks in the future.

Inclusive Team Culture

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

BASIC QUALIFICATIONS

- 2+ years of data scientist experience

- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience

- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience

PREFERRED QUALIFICATIONS

- AWS Certifications, for example AWS Solution Architect Associate/Professional, ML Specialty, or Developer Associate

- Experience working with at least one of the following industry standard formats in an imagery domain: Satellite Imagery (NITF, GeoTIFF, SICD, etc.), Motion Imagery (commercial and USG FMV specs), or medical imagery (e.g. DICOM)

- Hands-on experience with state-of-the-art object detection approaches

- Experience managing multiple AWS and ML Environments through Infrastructure as code (Cloudformation, Cloud Development Kit, Terraform, Pulumi, etc.)

- 1+ years of experience with AWS services like SageMaker, S3, Fargate, DynamoDB, and/or Rekognition

- 2+ years of experience handling terabyte-scale datasets

- Experience containerizing/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

- A track record of deploying and managing models in production

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.

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