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AI Engineer

Job ID: ATR 17680

Job Description

Job Title: AI Engineer

Eligibility: Candidate must possess an active TS/SCI with Full Scope

Polygraph clearance

Job Description:

An active Top Secret/SCI Clearance with a Full Scope Polygraph is

required.

This job is onsite in Annapolis Junction, MD with 1-2 remote days/week

depending on tasking.

We have an immediate need for an Artificial Intelligence (AI) Engineer

who will work closely with system and software engineers to design,

prototype, and integrate AI advancements into the existing RAD

architecture. This is a transformative position focused on building

solutions that augment human intelligence, streamline workflows, and

enhance the overall effectiveness of intelligence operations.

Required technical skills and responsibilities include:

Design and Development: Lead the design and development of AI-driven

solutions from conception to deployment, ensuring seamless integration

with the existing software architecture. This includes prototyping new

models, writing production-quality code, and maintaining existing AI

systems.

Collaboration and Communication: Serve as a key technical liaison,

collaborating with cross-functional teams including system engineers,

software developers, and domain experts. Effectively present and

articulate recommended AI approaches, discussing the tradeoffs and

implications of different implementations with both technical and

non-technical stakeholders.

Data Analysis and Modeling: Conduct Exploratory Data Analysis (EDA) on

diverse datasets (both structured and unstructured) to inform the data

model, identify data quality issues, and determine optimal input

formats for AI models.

Model Building and Evaluation: Develop, train, and evaluate a variety

of machine learning models, ensuring they meet performance and

reliability requirements. Implement robust testing and validation

strategies to ensure models are accurate and unbiased.

Continuous Improvement: Stay current with the latest advancements in

AI and machine learning, continuously seeking opportunities to apply

new technologies and methodologies to improve existing systems and

solve complex problems.

Cloud Platforms: Have experience with the Amazon Web Services (AWS)

cloud computing platform and machine learning operations (MLOps) tools

for deploying and managing machine learning models at scale.

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