Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Chantilly, VA, United States
Actively hiring, first seen by us 6 days agoSAIC 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. Responsibilities include, but are not limited to:Read the full posting
Active Top Secret clearance with the ability to obtain SCI access
Design, code and deploy AI/ML prototypes for IC mission needs
Set up and maintain development environments for unclassified and SCIF work
Containerize applications and package models for secure deployment
Integrate prototypes into CI/CD pipelines and cloud environments
Prepare prototype environments and clean code for customer demos
Assist senior developers in designing, coding, and deploying visual AI/ML prototypes
Help configure and maintain development environments and local tooling for both unclassified and SCIF-based AI development
containerize applications (e.g., Docker) and package models for deployment into secure environments
Assist in integrating prototypes into CI/CD pipelines
Prepare prototype environments for customer demonstrations and ensure codebases are clean, well-structured, and well-commented
Ability to commute to Northern Virginia-area SAIC and customer facilities and to travel occasionally to other customer sites as required by the program.
Familiarity with Docker and basic cloud concepts in AWS and/or Azure.
Ability to sit or stand for extended periods while working at a computer workstation.
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.
- 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).
Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Day 6
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- 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.
- 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.
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.
- 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).
- 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:
- 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.
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We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
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.
Responsibilities include, but are not limited to:
Clearance Requirements:
Preferred Qualifications:
Physical Requirements:
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No pay amount identified in the saved description.
Chantilly, VA, United States
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. Responsibilities include, but are not limited to:
- Documentation: Draft clear technical documentation, API guides, and system diagrams to support the transition of prototypes into operational systems. - 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
No clear work-authorization passage found. Eligibility is unconfirmed.