Data Engineer

Key Skills

Data science techniques, Deep Learning, ETL frameworks, Git, Kubeflow, Linux Operating system, Machine learning techniques, Planning and organization, Python Programming, PyTorch, Scikit-learn

Job Description

As a Data Engineer, you 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 understand object detection robustness. This requires careful curation of data as well as development and curation of synthetic data. Additionally, you will contribute to the program’s source code, implementing data curation and data science techniques.

Our delivery teams are driven to explore new ideas and technology, and care deeply about collaboration, feedback, and iteration. We follow 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.

If cutting edge data science projects resonate with you, and you care deeply about joining a mission-driven company with a strong growth direction and diverse culture, we'd love to learn more about you. Check out the details below, and let’s connect.

Technical members of our solutions teams require little guidance, but love to learn, collaborate, and problem solve. This position requires a mid to senior level of experience, a passion for mission support, and a strong desire to solve our customers’ hardest technical and data challenges.

Location/Flexibility: Hybrid-Remote with some on-site work required in Vienna and Chantilly, VA

The Data Engineer will be responsible for the following:

• 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
• Implement source code and code provided by the data science team

Qualifications:

• You have 4+ years of experience designing and implementing data curation techniques specifically those designed for imagery
• You have built and maintained ETL pipelines and are experienced with Kubeflow pipelines
• You have worked with imagery data, overhead imagery (optical or Synthetic Aperture Radar (SAR)), and synthetic data.
• You understand large-scale distributed processing
• You think critically about hard problems
• You enjoy building data pipelines in ML frameworks
• You desire a fast-paced, collaborative, Agile environment
• You are familiar with machine and deep learning libraries such as Scikit-learn and PyTorch
• You are proficient with the Python programming language
• You have worked with Git version control systems
• You are no stranger to the Linux OS

Physical Requirements:

• Prolonged periods sitting at a desk and working on a computer.
• Must be able to lift up to 10-15 pounds at times.