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# AI/ML Developer

- **Company:** Science Applications International Corporation
- **Location:** Reston, VA, United States
- **Salary:** $120,001.0 - $160,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Clean Code Principles, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, Unit Testing, Microsoft Azure, Cloud Computing, System Configuration, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Software Engineering, Cloud Platform System, Pytorch, ReactJS, Large Language Models, Software Security, Git, Information Technology, Enterprise Integration, Operational Systems, Machine Learning Operations, Front End Software Development, Software Version Control, Docker
- **Published:** October 30, 2026
- **Apply:** https://dejobs.org/x/x/0C40570A257A42D5B42236171910597E/job/

## About the Role

* Residency in the Northern Virginia corridor with the ability to support a hybrid work model (remote plus on-site SCIF/customer locations as required).
 * Active Top Secret clearance with the ability to obtain SCI access
 * Bachelor's degree in Computer Science, Data Science, Engineering, or related technical discipline and 2+ years of relevant software or AI/ML experience;
 * OR Master's degree in a related technical discipline with 0+ years of relevant experience.
 * Foundational proficiency in Python and core software engineering practices (e.g., Git-based version control, unit testing, clean code architectures).
 * Hands-on exposure to at least one major ML framework (e.g., PyTorch or TensorFlow) through coursework, personal projects, internships, or professional tasks.

Clearance Requirements:

 * Active Top Secret clearance with the ability to obtain SCI access.
 * TS/SCI strongly preferred and may be required for specific program tasking.

Preferred Qualifications:

 * Familiarity with Docker and basic cloud concepts in AWS and/or Azure.
 * Experience using lightweight frontend tools or frameworks (e.g., React) to build functional, interactive user interfaces for demonstrations.
 * Familiarity with Intelligence Community missions, environments, and workflows.

Physical Requirements:

 * Works primarily in an office, lab, or SCIF environment using computers and standard office equipment.
 * Ability to sit or stand for extended periods while working at a computer workstation.
 * May require occasional lifting of laptops and related equipment (up to ~20 lbs).
 * Ability to commute to Northern Virginia-area SAIC and customer facilities and to travel occasionally to other customer sites as required by the program.

## Description

SAIC is building an early-career AI/ML Developer team within our Solutions and Technology Group, reporting to the Intel Space CTO. In this matrixed role, you will support the creation, prototyping, and operationalization of cutting-edge AI/ML Proof of Concepts (PoCs)-including GenAI/LLMs, NLP, and computer vision-specifically tailored to Intelligence Community (IC) mission use cases. These are dynamic, high-impact positions supporting multiple IC programs in both unclassified and classified environments. This is a hybrid role for candidates residing in the Northern Virginia corridor, with on-site work in SCIFs and customer facilities as needed., * Rapid PoC & demo prototyping ( 50%): Assist senior developers in designing, coding, and deploying visual AI/ML prototypes (GenAI/LLMs, NLP, computer vision) to address IC mission needs.

 * Environment setup: Help configure and maintain development environments and local tooling for both unclassified and SCIF-based AI development.
 * Secure deployment & MLOps ( 30%): Collaborate with senior engineers to containerize applications (e.g., Docker) and package models for deployment into secure environments.
 * Pipeline integration: Assist in integrating prototypes into CI/CD pipelines and deploying them into secure, multi-tenant cloud environments (AWS and/or Azure).
 * Demos & stakeholder support ( 20%): Prepare prototype environments for customer demonstrations and ensure codebases are clean, well-structured, and well-commented.
 * Documentation: Draft clear technical documentation, API guides, and system diagrams to support the transition of prototypes into operational systems.