Artificial Intelligence / Machine Learning Data Engineer

MAG Aerospace; Fairfax (VA); Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Flexible work arrangements

Remote work options

Occasional field exercises

Job summary

MAG Aerospace seeks an Artificial Intelligence / Machine Learning Data Engineer to lead data-driven AI solutions supporting tactical operations. You will handle multi-modal data, edge CV, RAG, and conversational AI while managing data pipelines in challenging environments.

US citizen with Secret clearance preferred; hybrid work with proximity to Fairfax, VA. Responsibilities include building data-centric AI systems, deploying edge models, and maintaining data governance across datasets and

Qualifications

• 5+ years experience in ML, AI, and data engineering.
• Strong Python and ML framework skills (PyTorch, TensorFlow, JAX).
• Experience with modern AI paradigms (transformers, diffusion models, neural ODEs).
• Hands-on LLM deployment/optimization (vLLM, TGI, llama.cpp).
• Proficiency with Spark, Airflow, dbt; SQL and NoSQL databases.
• Vector databases (Pinecone/Weaviate/pgvector) knowledge.

Responsibilities

• Develop data-centric AI solutions including computer vision pipelines.
• Implement RAG systems, agentic workflows, and fine-tuned LLMs.
• Design edge-optimized models using TensorRT/ONNX.
• Build ETL/data pipelines for feature engineering and model training.
• Create BI dashboards for operational insights.
• Implement multi-modal sensor fusion algorithms.
• Maintain data lakes/warehouses and real-time streaming.
• Develop conversational AI interfaces using open-source LLMs.
• Enforce data quality, governance, and lifecycle validation.
• Optimize AI workloads for embedded platforms; CUDA acceleration.
• Profile memory/power on edge devices; support embedded systems.

Skills

ML/Data engineering

Python

PyTorch

TensorFlow

JAX

Transformers

Diffusion models

Neural ODEs

LLM deployment

Apache Spark

Airflow

dbt

SQL

NoSQL

Pinecone

Weaviate

pgvector

OpenCV

Video processing

MLOps

LangChain

AutoGPT

CrewAI

Defense AI

llama.cpp

vLLM

TGI

Education

Bachelor's degree in CS/EE

Master's degree preferred

Tools

TensorRT

ONNX

quantization

llama.cpp

vLLM

TGI

Job description

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. 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

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