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AI Engineer (40% Telework) with Security Clearance

MasterPeace Solutions, Ltd.Fort Meade, MD🇺🇸United StatesPosted 13 Jul 2026

Why This Role Stands Out

This AI Engineer role offers a fantastic opportunity to lead the design and development of cutting-edge AI solutions, leveraging your expertise in machine learning and cloud platforms. You'll thrive here if you're a collaborative problem-solver eager to make a significant impact while enjoying the flexibility of a hybrid work arrangement, so don't miss out on this exciting chance to grow your career.

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
Fort Meade, MD, United States
Posted
6 weeks ago
AWSMLOpsMachine Learning

Job Description

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.
  • 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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