Software Engineer: ML & Simulation for National Defense

Radiance Technologies; Dahlgren (VA); On-site; USD 120,000 - 170,000; Full time

Job summary

Radiance Technologies is seeking a Software Engineer to join our Enhanced Modeling and Simulation team. You’ll collaborate with software engineers, data scientists, and operations research analysts to support national defense and partner platforms.

The role emphasizes ML and modeling with full lifecycle development, from prototyping to deployment, using C++/Java, Python/R, and containerized ecosystems like Docker and Kubernetes.

Qualifications

• Bachelor’s degree or higher in CS/CE or related field with ≥30 semester hours in math, statistics, and CS.
• Four+ years of full lifecycle software development for constructive simulation (AFSIM/ITASE/NGTS).
• Proficient in C++ and/or Java; scripting in Python or R.
• Experience with modeling networks and building data pipelines for ETL.
• Familiar with Docker, Kubernetes, CI/CD, and regression testing.

Responsibilities

• Research, develop, and deploy ML algorithms for software and hardware applications.
• Design and optimize systems using mathematical modeling.
• Analyze complex datasets to develop high-performance software solutions.
• Build tools and systems to support software testing, validation, and performance benchmarking.
• Collaborate with cross-functional teams to integrate modeling and simulation capabilities into DoD platforms.

Skills

Machine learning

C++

Java

Python

R scripting

Docker

Kubernetes

TS/SCI clearance

Full-stack

Data pipelines

Network modeling

CI/CD

Education

Bachelor’s degree in CS/CE or related field with ≥30 semester hours in math, statistics, and CS

Tools

Docker

Kubernetes

Visual Studio

Visual Studio Code

PyCharm

Git

Job description

Radiance Technologies is seeking a Software Engineer to join our Enhanced Modeling and Simulation team. You’ll collaborate with software engineers, data scientists, and operations research analysts to support national defense and partner platforms.

The role emphasizes ML and modeling with full lifecycle development, from prototyping to deployment, using C++/Java, Python/R, and containerized ecosystems like Docker and Kubernetes.