Position Summary
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. Youll 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 the most challenging environments. While youll have a core expertise in either data engineering or model development you have a passion for mastering the full stack of AI systems.
US Citizens Only
Former US Defense Contractor / US Gov / US Military Experience Only
This is a Hybrid Position - Remote mainly - but as well on call to come into a MAG office when requested
We are seeking candidates who live in proximity to our corporate HQ in Fairfax VA primarily but will entertain persons living near our satellite offices in:
Aberdeen MD - Titusville FL - Newport News VA - Carthage NC
Essential Duties and Responsibilities
Duties include but not limited to:
Primary 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:
- Optimize AI workloads for embedded platforms (Jetson Intel Neural Compute Stick)
- Implement hardware acceleration using CUDA and TensorRT
- Profile and optimize memory/power consumption for edge devices
- Support embedded systems team with AI-specific hardware integration
- Design distributed inference systems for degraded network conditions
Requirements
Minimum Requirements:
Primary Experience / 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 )
- 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 business intelligence 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 and tools (e.g. MLflow Kubeflow Weights & Biases)
- Published research or patents in relevant areas
Education & Experience:
- Bachelors degree in CS EE or related field;
- Masters preferred
Clearance:
- Must be eligible for Secret security clearance
Other Qualifications:
Special Note
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
Company Policy
Position SummaryMAG 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. Youll leverage COTS FOSS/OSS and custo...
Position Summary
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. Youll 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 the most challenging environments. While youll have a core expertise in either data engineering or model development you have a passion for mastering the full stack of AI systems.
US Citizens Only
Former US Defense Contractor / US Gov / US Military Experience Only
This is a Hybrid Position - Remote mainly - but as well on call to come into a MAG office when requested
We are seeking candidates who live in proximity to our corporate HQ in Fairfax VA primarily but will entertain persons living near our satellite offices in:
Aberdeen MD - Titusville FL - Newport News VA - Carthage NC
Essential Duties and Responsibilities
Duties include but not limited to:
Primary 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:
- Optimize AI workloads for embedded platforms (Jetson Intel Neural Compute Stick)
- Implement hardware acceleration using CUDA and TensorRT
- Profile and optimize memory/power consumption for edge devices
- Support embedded systems team with AI-specific hardware integration
- Design distributed inference systems for degraded network conditions
Requirements
Minimum Requirements:
Primary Experience / 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 )
- 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 business intelligence 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 and tools (e.g. MLflow Kubeflow Weights & Biases)
- Published research or patents in relevant areas
Education & Experience:
- Bachelors degree in CS EE or related field;
- Masters preferred
Clearance:
- Must be eligible for Secret security clearance
Other Qualifications:
Special Note
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
Company Policy
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