Description

As a Data Engineer, candiate will have the unique opportunity to curate and organize data for a program advancing state-of-the-art modeling and prediction capabilities. The aim of this program is to discover and curate data as well as develop and curate synthetic data. Then, develop machine learning (ML) models and training pipelines to detect and discern features in scenes. Finally, inject obfuscations into the data to fool the models.

 

The delivery teams are driven to explore new ideas and technology, and care deeply about collaboration, feedback, and iteration. The team follows SAFe agile practices, embrace the Ops ethos (DataOps/DevSecOps/MLOps) to “automate-first”, use modern tech stacks, and constantly challenge each other to grow and improve.

 

Assess, transform, organize, and optimize data for use by machine learning algorithms

Generating representative data sets for systems development and data science initiatives

Build data pipelines that enables data scientists and engineers and other stakeholders

Position Type
Full-time

Location
VA

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Qualifications
Demonstrated experience building and maintaining ETL pipelines.

Demonstrated experience working with Synthetic Aperture Radar (SAR) data

Demonstrated experience with large-scale distributed processing

Experience building data pipelines in ML frameworks. Kubeflow experience is desired

Requirements
TS/SCI clearance required

Experience
4+ years of experience designing data models and data warehouses supporting analytics, using both relational and non-relational distributed data storage systems

Experience with Apache Beam

Experience working in a fast-paced agile environment

Education

Any graduate