AI ML Engineer Principal

Posted 3 days agoViewed

💎 Seniority level: Principal, 14 years

📍 Location: US

🔍 Industry: Engineering and Sciences

⏳ Experience: 14 years

🪄 Skills: AWSLeadershipProject ManagementPythonSQLApache HadoopArtificial IntelligenceCloud ComputingCybersecurityData AnalysisKerasMachine LearningNumpyPyTorchC++TableauAlgorithmsApache KafkaData engineeringData scienceData StructuresREST APITensorflowCommunication SkillsAnalytical SkillsCollaborationCI/CDProblem SolvingMicrosoft OfficeAgile methodologiesLinuxWritten communicationCritical thinkingActive listeningData visualizationTeam managementData modelingScriptingData analyticsData managementDebugging

Requirements:

Active Top Secret Clearance with the ability to obtain a TS/SCI.
Bachelor’s degree in Data Science, Computer Science, Engineering, or related field.
14 years of experience in Data Collection, Processing, or Analysis systems.
5 years of experience with classified DoD/IC systems and AI/ML development.
5 years of experience leading technical teams.
Experience with AI/ML frameworks (TensorFlow, Keras, PyTorch).
Experience with programming in Python, R, C++, or similar.
Experience using analytics and visualization tools (Tableau, Power BI, matplotlib, Plotly).
Experience in big data solutions (Accumulo, Hadoop, Spark, Kafka).
DoD 8570/8140 certifications or equivalent in Information Assurance and Cybersecurity (e.g., Security+ or higher).

Responsibilities:

Design, build, and maintain ML/DL models for various AI applications in classified environments.
Leverage the Enterprise Data Architecture for secure and efficient data management.
Collaborate with cross-functional teams to test, validate, and deploy AI/ML models.
Enhance system performance through AI/ML models and big data engineering.
Analyze large datasets to identify patterns and insights.
Design and manage data pipelines for rapid prototyping.
Implement data visualization and UX solutions to enhance user experience.
Apply zero-trust principles in data security and management.
Develop solutions for MLS systems, integrating data from different security enclaves.
Translate mission needs into analytical approaches to achieve mission outcomes.
Perform data collection, cleansing, integration, and storage in classified settings.
Ensure AI solutions comply with privacy regulations and ethical AI standards.
Implement monitoring for AI model performance.
Build trust and "explainability" in AI, ensuring transparent processes.
Stay updated with AI/ML advancements and incorporate them into operations.
Manage and support a team of engineers, fostering a collaborative environment

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