Blueprint Creative Group
Machine Learning Engineer (Federal Sector)
Blueprint Creative Group, Poland, New York, United States
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
Develop and deploy machine learning models
for anomaly detection, risk assessment, and predictive modeling in federal environments.
Optimize AI‑powered cybersecurity solutions
for threat detection and vulnerability assessments.
Enhance geospatial intelligence analytics
by refining object detection, data fusion, and predictive mapping techniques.
Implement and fine‑tune deep learning frameworks
such as
TensorFlow, PyTorch, and Scikit‑Learn .
Design AI‑driven dashboards and analytics tools
using
Tableau, Power BI, or D3.js
for real‑time federal data insights.
Ensure AI compliance
with
FedRAMP, Zero Trust, NIST AI ethics, and CISA cybersecurity guidelines .
Collaborate with federal agencies and technology teams
to align AI solutions with mission objectives.
Required Skills & Experience
3+ years
of experience in
machine learning, predictive analytics, or AI model deployment .
Strong programming skills
in
Python, R, and SQL ; familiarity with cloud AI tools like
AWS SageMaker, Azure AI, or Google Vertex AI .
Experience working on
federal data analytics, cybersecurity, or risk intelligence projects .
Proficiency in data visualization tools
such as
Tableau, Power BI, or D3.js .
Familiarity with
Zero Trust frameworks, NIST AI Risk Management Framework, and federal cybersecurity best practices .
Experience in
natural language processing (NLP), computer vision, or reinforcement learning (preferred but not required).
Security Clearance
Preferred:
Secret / TS/SCI (for DoD‑related projects).
Location
Remote / Hybrid
(with potential travel to federal agency sites).
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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
Develop and deploy machine learning models
for anomaly detection, risk assessment, and predictive modeling in federal environments.
Optimize AI‑powered cybersecurity solutions
for threat detection and vulnerability assessments.
Enhance geospatial intelligence analytics
by refining object detection, data fusion, and predictive mapping techniques.
Implement and fine‑tune deep learning frameworks
such as
TensorFlow, PyTorch, and Scikit‑Learn .
Design AI‑driven dashboards and analytics tools
using
Tableau, Power BI, or D3.js
for real‑time federal data insights.
Ensure AI compliance
with
FedRAMP, Zero Trust, NIST AI ethics, and CISA cybersecurity guidelines .
Collaborate with federal agencies and technology teams
to align AI solutions with mission objectives.
Required Skills & Experience
3+ years
of experience in
machine learning, predictive analytics, or AI model deployment .
Strong programming skills
in
Python, R, and SQL ; familiarity with cloud AI tools like
AWS SageMaker, Azure AI, or Google Vertex AI .
Experience working on
federal data analytics, cybersecurity, or risk intelligence projects .
Proficiency in data visualization tools
such as
Tableau, Power BI, or D3.js .
Familiarity with
Zero Trust frameworks, NIST AI Risk Management Framework, and federal cybersecurity best practices .
Experience in
natural language processing (NLP), computer vision, or reinforcement learning (preferred but not required).
Security Clearance
Preferred:
Secret / TS/SCI (for DoD‑related projects).
Location
Remote / Hybrid
(with potential travel to federal agency sites).
#J-18808-Ljbffr