AI/ML Engineer/Data Scientist / Public Trust

Peraton; Virginia (MN); On-site; USD 120,000 - 180,000; Full time

Job summary

Peraton is seeking an experienced AI/ML Data Scientist to join the Federal Strategic Cyber program in Warrenton, VA. You will design and maintain ETL pipelines, translate raw data into standardized formats, and develop AI models to refine data and enable alerting.

You will implement containerization with OpenShift/Kubernetes, integrate CI/CD into the SDLC, and monitor performance, security, and availability across environments. Strong collaboration with clients and technical teams is required.

Qualifications

• Bachelor’s degree with 8+ years relevant technical experience, or 4 additional years in lieu of degree.
• Fluent in AI/ML techniques and ability to apply them to data science problems.
• Strong scripting skills (Bash, Python) for automation and ETL pipelines.
• Solid understanding of containerization (Docker, Podman) and orchestration (OpenShift/Kubernetes).
• U.S. Citizenship and ability to obtain Public Trust clearance.
• Willingness to travel 10–25% and collaborate with clients and cross-functional teams.

Responsibilities

• Design, build, and maintain ETL pipelines using Python to convert raw data into standardized schemas.
• Develop and optimize AI/ML models to explore data and support normalization and alerting.
• Implement containerization strategies with OpenShift/Kubernetes and CI/CD integration.
• Monitor system performance, reliability, and security across development to production.
• Troubleshoot and resolve issues in development, test, and production environments.
• Interface with clients and technical staff to ensure efficient, secure service delivery.

Skills

AI/ML techniques

Scripting (Bash, Python)

Team collaboration

Client interfacing

Education

Bachelor’s degree

Tools

Docker

Podman

OpenShift

Kubernetes

Job description

Required

• Bachelor’s degree and a minimum of 8 years related technical experience required.
  • An additional 4 years of experience may be substituted in lieu of a degree.
• Demonstrated fluency in AI/ML techniques.
• Proficiency in scripting and automation (Bash, Python, etc.).
• Strong understanding of containerization principles (Docker, Podman, etc.).
• Ability to work independently and collaboratively in a team environment.
• Experience interfacing with clients, technical support personnel, and other technical professionals to ensure efficient and effective service.
• U.S. Citizenship is required.
• Ability to obtain a Public Trust security clearance required.
• Willingness and ability to travel 10-25%.

Preferred

• Experience with the Databricks Data and AI platform.
• Proven experience with OpenShift and Kubernetes in production environments.
• Experience with Openshift/Kubernetes and other container-based platforms.
• Experience implementing and utilizing AI models to explore and refine data.
• Experience training task specific AI models for normalization and alerting.
• Experience with SAFe Agile testing environments.
• Experience using OpenShift to run microservice architectures designed to manage scale of data transformation processes.

Position Description

• Peraton is currently seeking to hire an experienced AI/ML DataScientist to join our Federal Strategic Cyber program.
• Location: Warrenton, VA
• Expertise and fluency in AI/ML techniques.
• Design, build, and maintain Extract, Transform, and Load (ETL) pipelines using industry best practices.
• Work with data management teams to design transform scripts in languages like Python to convert raw data to standardized data schemas.
• Implement and manage containerization strategies using OpenShift/Kubernetes.
• Collaborate with development teams to integrate CI/CD pipelines into the software development lifecycle.
• Monitor and optimize system performance, reliability, and availability.
• Automate infrastructure and application deployment processes.
• Ensure security best practices are implemented throughout all DevOps procedures.
• Troubleshoot and resolve issues in development, test, and production environments.