
AI/ML Developer
Reston, VA · HybridJob$120–160K/yrSeen 5 days agoSeen in employer's feed 4 days ago
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At a glance
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Requirements
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Job overview
SAIC is building an early-career AI/ML Developer team in its Solutions and Technology Group to create, prototype, and operationalize AI/ML proof-of-concepts for Intelligence Community missions. The role supports multiple programs in unclassified and classified environments, working with senior developers and engineers on prototypes, secure deployment, pipeline integration, and customer demonstrations. It is hybrid for candidates residing in the Northern Virginia corridor, with on-site work in SCIFs and customer facilities as needed.
Skills & qualifications
Skills
Qualifications
Full job description
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.
Responsibilities include, but are not limited to:
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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.
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Environment setup: Help configure and maintain development environments and local tooling for both unclassified and SCIF-based AI development.
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Secure deployment & MLOps (≈30%): Collaborate with senior engineers to containerize applications (e.g., Docker) and package models for deployment into secure environments.
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Pipeline integration: Assist in integrating prototypes into CI/CD pipelines and deploying them into secure, multi-tenant cloud environments (AWS and/or Azure).
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Demos & stakeholder support (≈20%): Prepare prototype environments for customer demonstrations and ensure codebases are clean, well-structured, and well-commented.
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Documentation: Draft clear technical documentation, API guides, and system diagrams to support the transition of prototypes into operational systems.
Qualifications
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Residency in the Northern Virginia corridor with the ability to support a hybrid work model (remote plus on-site SCIF/customer locations as required).
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Active Top Secret clearance with the ability to obtain SCI access.
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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.
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OR Master’s degree in a related technical discipline with 0+ years of relevant experience.
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Foundational proficiency in Python and core software engineering practices (e.g., Git-based version control, unit testing, clean code architectures).
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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:
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Active Top Secret clearance with the ability to obtain SCI access.
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TS/SCI strongly preferred and may be required for specific program tasking.
Preferred Qualifications:
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Familiarity with Docker and basic cloud concepts in AWS and/or Azure.
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Experience using lightweight frontend tools or frameworks (e.g., React) to build functional, interactive user interfaces for demonstrations.
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Familiarity with Intelligence Community missions, environments, and workflows.
Physical Requirements:
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Works primarily in an office, lab, or SCIF environment using computers and standard office equipment.
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Ability to sit or stand for extended periods while working at a computer workstation.
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May require occasional lifting of laptops and related equipment (up to ~20 lbs).
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Ability to commute to Northern Virginia-area SAIC and customer facilities and to travel occasionally to other customer sites as required by the program.
Target salary range: $120,001 - $160,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.
REQNUMBER: 2618534
SAIC is a premier technology integrator, solving our nation's most complex modernization and systems engineering challenges across the defense, space, federal civilian, and intelligence markets. Our robust portfolio of offerings includes high-end solutions in systems engineering and integration; enterprise IT, including cloud services; cyber; software; advanced analytics and simulation; and training. We are a team of 23,000 strong driven by mission, united purpose, and inspired by opportunity. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $6.5 billion. For more information, visit saic.com. For information on the benefits SAIC offers, see Working at SAIC. EOE AA M/F/Vet/Disability
How this job compares
Set against the 6,099 open Machine Learning Engineer jobs on Olive Jobs, counted November 3, 2026.
- Pay
- This posting$120–160K/yr
- Virginia median$131–210K/yr227 salary ranges
- US median$148–245K/yr4,859 salary ranges
This range's midpoint, $140K, is 21% below the Virginia median midpoint ($178K) — in the lowest quarter of Machine Learning Engineer salary ranges in Virginia.
- Openings
- Olive Jobs lists 267 open Machine Learning Engineer jobs in Virginia and 6,099 across the US. 8% of them nationwide are listed as remote or flexible.
- Hiring the most in Virginia
- Capital One55 open
- Amazon38 open
- EY17 open
- Experience
- This posting asks for no prior experience — less than three in four Machine Learning Engineer postings that state a minimum ask for (median 5 years, across 4,881 postings).
- Education
- 2,296 of the 6,099 open Machine Learning Engineer jobs (38%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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