MAG Aerospace
Artificial Intelligence / Machine Learning Data Engineer
MAG Aerospace, Fairfax, Virginia, United States, 22032
Overview
Artificial Intelligence / Machine Learning Data Engineer. MAG Aerospace is staffing for a Artificial Intelligence / Machine Learning Data Engineer. This position will lead the development of intelligent systems that transform multi-modal sensor data into actionable intelligence for tactical operations. You will leverage COTS, FOSS/OSS, and custom development to build or integrate everything from edge computer vision to conversational AI assistants, while managing the data pipelines that feed these systems in challenging environments. You will have a core expertise in either data engineering or model development and a passion for mastering the full AI stack. Essential Duties and Responsibilities
Develop and optimize data-centric AI solutions such as computer vision pipelines for object detection, tracking, and classification Implement advanced AI capabilities including RAG systems, agentic workflows, and fine-tuned LLMs Design and deploy edge-optimized models using TensorRT, ONNX, and quantization techniques Build data engineering pipelines for ETL, feature engineering, and model training Create analytics dashboards and business intelligence solutions for operational insights Implement multi-modal sensor fusion algorithms (visual, thermal, acoustic, RF) Design and maintain data lakes, warehouses, and real-time streaming architectures Develop conversational AI interfaces using open-source LLMs (Llama, Mistral, etc.) Establish and enforce data quality standards, validation checks, and governance procedures throughout the data lifecycle Develop and implement robust testing and validation strategies for AI/ML models, including performance under degraded data conditions, adversarial testing, and operational scenarios Secondary responsibilities include optimizing AI workloads for embedded platforms (Jetson, Intel Neural Compute Stick), implementing hardware acceleration using CUDA and TensorRT, profiling and optimizing memory/power consumption for edge devices, supporting embedded systems team with AI-specific hardware integration, and designing distributed inference systems for degraded network conditions Qualifications
5+ years’ experience in machine learning, AI, and data engineering Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX) Experience with modern AI paradigms (transformers, diffusion models, neural ODEs) Hands-on experience with LLM deployment and optimization (vLLM, TGI, llama.cpp) Proficiency with data engineering tools (Apache Spark, Airflow, dbt, etc.) Experience with both SQL and NoSQL databases at scale Knowledge of vector databases and embedding systems (Pinecone, Weaviate, pgvector) Experience with computer vision libraries (OpenCV, PIL) and video processing Understanding of MLOps practices and model lifecycle management Preferred qualifications: experience with military/defense AI applications; knowledge of agentic AI frameworks (LangChain, AutoGPT, CrewAI); familiarity with federated learning and edge-cloud hybrid architectures; experience with BI tools (Tableau, PowerBI, Grafana); knowledge of time-series analysis and anomaly detection; experience with knowledge graphs and semantic reasoning; understanding of explainable AI and model interpretability; experience with MLOps platforms (MLflow, Kubeflow, Weights & Biases); published research or patents in relevant areas Education & Experience
Bachelor\'s degree in CS, EE, or related field; Master\'s preferred Clearance
Must be eligible for Secret security clearance Other Qualifications
Must be a US citizen What Makes You Successful Here
You can build anything from a computer vision pipeline to a conversational AI assistant You treat data engineering as seriously as model development You understand the tradeoffs between cloud-scale and edge deployment You can explain complex AI concepts to operators and executives alike You see AI as a tool for augmenting human decision-making, not replacing it Why Join MAG
Work on meaningful problems that directly impact national security Small, elite team where your contributions matter immediately Access to cutting-edge hardware and technologies Rapid prototyping environment - see your ideas deployed in weeks Direct interaction with end users and field deployments Professional development and conference attendance support Flexible work arrangements with occasional field exercises Opportunity to shape the future of tactical edge computing Policy and Accessibility
MAG Aerospace is an Equal Opportunity/Affirmative Action Employer and is committed to Diversity and Inclusion. We encourage diverse candidates to apply. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. MAG provides reasonable accommodation to applicants under applicable laws. If you need assistance due to a disability, please contact the MAG Aerospace Recruiting email or phone listed in the posting.
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Artificial Intelligence / Machine Learning Data Engineer. MAG Aerospace is staffing for a Artificial Intelligence / Machine Learning Data Engineer. This position will lead the development of intelligent systems that transform multi-modal sensor data into actionable intelligence for tactical operations. You will leverage COTS, FOSS/OSS, and custom development to build or integrate everything from edge computer vision to conversational AI assistants, while managing the data pipelines that feed these systems in challenging environments. You will have a core expertise in either data engineering or model development and a passion for mastering the full AI stack. Essential Duties and Responsibilities
Develop and optimize data-centric AI solutions such as computer vision pipelines for object detection, tracking, and classification Implement advanced AI capabilities including RAG systems, agentic workflows, and fine-tuned LLMs Design and deploy edge-optimized models using TensorRT, ONNX, and quantization techniques Build data engineering pipelines for ETL, feature engineering, and model training Create analytics dashboards and business intelligence solutions for operational insights Implement multi-modal sensor fusion algorithms (visual, thermal, acoustic, RF) Design and maintain data lakes, warehouses, and real-time streaming architectures Develop conversational AI interfaces using open-source LLMs (Llama, Mistral, etc.) Establish and enforce data quality standards, validation checks, and governance procedures throughout the data lifecycle Develop and implement robust testing and validation strategies for AI/ML models, including performance under degraded data conditions, adversarial testing, and operational scenarios Secondary responsibilities include optimizing AI workloads for embedded platforms (Jetson, Intel Neural Compute Stick), implementing hardware acceleration using CUDA and TensorRT, profiling and optimizing memory/power consumption for edge devices, supporting embedded systems team with AI-specific hardware integration, and designing distributed inference systems for degraded network conditions Qualifications
5+ years’ experience in machine learning, AI, and data engineering Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX) Experience with modern AI paradigms (transformers, diffusion models, neural ODEs) Hands-on experience with LLM deployment and optimization (vLLM, TGI, llama.cpp) Proficiency with data engineering tools (Apache Spark, Airflow, dbt, etc.) Experience with both SQL and NoSQL databases at scale Knowledge of vector databases and embedding systems (Pinecone, Weaviate, pgvector) Experience with computer vision libraries (OpenCV, PIL) and video processing Understanding of MLOps practices and model lifecycle management Preferred qualifications: experience with military/defense AI applications; knowledge of agentic AI frameworks (LangChain, AutoGPT, CrewAI); familiarity with federated learning and edge-cloud hybrid architectures; experience with BI tools (Tableau, PowerBI, Grafana); knowledge of time-series analysis and anomaly detection; experience with knowledge graphs and semantic reasoning; understanding of explainable AI and model interpretability; experience with MLOps platforms (MLflow, Kubeflow, Weights & Biases); published research or patents in relevant areas Education & Experience
Bachelor\'s degree in CS, EE, or related field; Master\'s preferred Clearance
Must be eligible for Secret security clearance Other Qualifications
Must be a US citizen What Makes You Successful Here
You can build anything from a computer vision pipeline to a conversational AI assistant You treat data engineering as seriously as model development You understand the tradeoffs between cloud-scale and edge deployment You can explain complex AI concepts to operators and executives alike You see AI as a tool for augmenting human decision-making, not replacing it Why Join MAG
Work on meaningful problems that directly impact national security Small, elite team where your contributions matter immediately Access to cutting-edge hardware and technologies Rapid prototyping environment - see your ideas deployed in weeks Direct interaction with end users and field deployments Professional development and conference attendance support Flexible work arrangements with occasional field exercises Opportunity to shape the future of tactical edge computing Policy and Accessibility
MAG Aerospace is an Equal Opportunity/Affirmative Action Employer and is committed to Diversity and Inclusion. We encourage diverse candidates to apply. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. MAG provides reasonable accommodation to applicants under applicable laws. If you need assistance due to a disability, please contact the MAG Aerospace Recruiting email or phone listed in the posting.
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