Machine Learning Engineer (Federal Sector)
Company
Blueprint Creative Group
Location
Remote
Type
Full Time
Job Description
Machine Learning Engineer (Federal AI & Predictive Analytics)
Job Overview: Blueprint Creative Group is seeking a Machine Learning Engineer with a strong background in AI-driven predictive analytics and federal cybersecurity applications. This role focuses on developing training and deploying AI models for mission-critical applications including cybersecurity geospatial intelligence and risk analytics for federal agencies.
Key Responsibilities:
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Develop and deploy machine learning models for anomaly detection risk assessment and predictive modeling in federal environments.
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Optimize AI-powered cybersecurity solutions for threat detection and vulnerability assessments.
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Enhance geospatial intelligence analytics by refining object detection data fusion and predictive mapping techniques.
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Implement and fine-tune deep learning frameworks such as TensorFlow PyTorch and Scikit-Learn .
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Design AI-driven dashboards and analytics tools using Tableau Power BI or D3.js for real-time federal data insights.
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Ensure AI compliance with FedRAMP Zero Trust NIST AI ethics and CISA cybersecurity guidelines .
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Collaborate with federal agencies and technology teams to align AI solutions with mission objectives.
Required Skills & Experience:
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3+ years of experience in machine learning predictive analytics or AI model deployment .
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Strong programming skills in Python R and SQL ; familiarity with cloud AI tools like AWS SageMaker Azure AI or Google Vertex AI .
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Experience working on federal data analytics cybersecurity or risk intelligence projects .
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Proficiency in data visualization tools such as Tableau Power BI or D3.js .
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Familiarity with Zero Trust frameworks NIST AI Risk Management Framework and federal cybersecurity best practices .
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Experience in natural language processing (NLP) computer vision or reinforcement learning (preferred but not required).
Security Clearance:
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Preferred: Secret / TS/SCI (for DoD-related projects).
Location:
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Remote / Hybrid (with potential travel to federal agency sites).
Date Posted
11/08/2025
Views
0
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