Goforth Scientific, an innovative tech company, is looking for a Machine Learning Engineer to build custom cloud based data analytics for ATR and pattern matching in R&D and operational environments. The successful candidate will be expected to build, evaluate and maintain ML models and analytics. Challenge yourself with new ML/AI technologies and enhance your skills on an increasingly diverse set of projects for the enterprising candidate.

Key Skills and Qualities

• Advanced College degree or commensurate experience preferred.
• Knowledge of ML techniques and procedures (MLOps) required.
• Experience with Python, MATLAB, Java, SageMaker, Jupyter Notebooks, AWS cloud technologies are a plus.
• Willingness to learn new technologies is a plus.
• Customer relationship skills.
• Security clearance required or must be willing to take and pass security background investigation and polygraph if requested

Key responsibilities
• Design and create new models
• Build prototype analytics
• Evaluate and enhance current analytics

The Company
Goforth Scientific is a high-tech science and engineering company that builds fast and reliable data analytics software to extract geospatial intelligence with high-value customer impact.  We solve 21st century challenges ranging from national security problems to emerging threats. Our consulting services include web site design, image processing, advanced algorithm development for GIS applications and custom cloud-based software applications.

The Benefits
• 4 weeks PTO
• Retirement plan
• Company laptop
• Flexible work hours (Part-time and flexible hours will be considered)

How to apply
Contact us for more information and to submit your resume info@goforthsci.com.
Current as of 2022/11/01

Paragon is a software product developed for advanced analytics and large amounts of streaming data. Paragon can absorb many different streaming data sources and data types.

Paragon is fully automated. It runs on AWS in Docker containers. Paragon can be used to monitor commercial and industrial sites such as airports and plants for activity such as earthquakes and severe weather.

Results are sent as Alerts and can be sent out in a variety of formats: RSS, email, SMS, GoogleEarth live KML, or JSON messages over Kafka and ActiveMQ.