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'll 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 you'll 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, 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 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:

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

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

MAG Aerospace (MAG) is an Equal Opportunity/Affirmative Action Employer and is committed to Diversity and Inclusion. We encourage diverse candidates to apply to our positions.
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.

https://www.dol.gov/agencies/ofccp/posters

MAG Aerospace (MAG) is committed to providing an online application process that is accessible to all, including individuals with a disability, by offering an alternative way to apply for job openings. This alternative method is available for those who cannot otherwise complete the online application due to a disability or need for accommodation.
MAG provides reasonable accommodation to applicants under the guidance of the Americans with Disabilities Act (ADA), Section 503 of the Rehabilitation Act of 1973, the Vietnam-Era Veterans’ Readjustment Assistance Act of 1974, and certain state and/or local laws.

If you need assistance due to a disability, please contact the MAG Aerospace Recruiting email:
Applicant.Assist@magaero.com or call (703) 376-8993.

MAG Aerospace

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Artificial Intelligence / Machine Learning Data Engineer