Machine Learning Engineer, Computer Vision & Remote Sensing, Proserve

- Bachelor's degree in computer science or equivalent
- 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- 3+ years professional experience with enterprise programming applications (i.e. Python, Java or C++) and Linux (i.e. bash scripting, containers, GPU based server configurations etc.)
- 2+ years of cloud software development experience
- Current, active US Government Security Clearance of TS/SCI or above
- AWS and/or relative cloud certifications (i.e. AWS Solution Architect Associate/Professional, ML Specialty, or Developer Associate)
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience working with satellite imagery, aerial imagery, medical imagery, infrared imagery, or another “unusual” imagery data type
- Experience working in production ML environments including deploying computer vision models, specifically neural networks, into production environments using containers
- Experience with Infrastructure as Code (IaC) tools such as Terraform, Cloudformation or AWS Cloud Development Kit (CDK)
- 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

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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 also guide teams in the development of new solutions and aid customers in adopting AWS ML capabilities.

This position requires that the candidate selected must currently possess and maintain an active TS/SCI security clearance. The position further requires that, after start, the selected candidate obtain and maintain an active TS/SCI security clearance with polygraph or commensurate clearance for each government agency for which they perform AWS work.

Key job responsibilities
- 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.
- Implement Machine Learning Operations (MLOps) workflows such as model deployment, retraining, testing, and performance monitoring.
- 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 other 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 innovative internal algorithms for your customers.
- Experience applying best practices from core Software Development activities to Machine Learning (deployability, unit testing, well structured extensible software, etc.)

About the team
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.