About The Company
MAG Aerospace is a leading provider of innovative aerospace and defense solutions, specializing in advanced technology systems that support national security and tactical operations. Renowned for its commitment to excellence, MAG Aerospace leverages cutting-edge research, development, and engineering to deliver mission-critical capabilities to government and military clients. The company fosters a culture of innovation, collaboration, and integrity, ensuring its solutions meet the highest standards of quality and reliability. With a focus on developing transformative systems, MAG Aerospace is dedicated to pushing the boundaries of technology to address complex operational challenges across the globe.
About The Role
We are seeking a highly skilled Artificial Intelligence / Machine Learning Data Engineer to join our dynamic team. This position will be instrumental in leading the development of intelligent systems that convert multi-modal sensor data into actionable intelligence for tactical operations. The successful candidate will utilize a variety of tools, including commercial off-the-shelf (COTS), open-source software (FOSS/OSS), and custom solutions, to build and integrate systems ranging from edge computer vision to conversational AI assistants. This role involves managing data pipelines that support these systems, often in challenging environments. While the primary expertise may lie in either data engineering or model development, a passion for mastering the entire AI system stack is essential. The position offers a hybrid work environment, primarily remote, with on-call requirements to visit MAG offices as needed, primarily near Fairfax, VA, and other satellite locations.
Qualifications
- Minimum of 5+ years of experience in machine learning, AI, and data engineering
- Proficiency in Python programming language
- Experience with ML frameworks such as PyTorch, TensorFlow, JAX
- Hands-on experience with modern AI paradigms including transformers, diffusion models, and neural ODEs
- Experience deploying and optimizing large language models (LLMs) using tools like vLLM, TGI, llama.cpp
- Strong knowledge of data engineering tools such as Apache Spark, Airflow, and dbt
- Experience working with both SQL and NoSQL databases at scale
- Knowledge of vector databases and embedding systems like Pinecone, Weaviate, and pgvector
- Experience with computer vision libraries such as OpenCV and PIL, along with video processing expertise
- Understanding of MLOps practices and model lifecycle management
- Eligibility for Secret security clearance
- U.S. citizenship is mandatory
Responsibilities
- Develop and optimize data-centric AI solutions, including computer vision pipelines for object detection, tracking, and classification
- Implement advanced AI capabilities such as Retrieval-Augmented Generation (RAG) systems, agentic workflows, and fine-tuned large language models
- Design and deploy edge-optimized models utilizing TensorRT, ONNX, and quantization techniques
- Construct data engineering pipelines for ETL processes, feature engineering, and model training
- Create analytics dashboards and business intelligence solutions to provide operational insights
- Implement multi-modal sensor fusion algorithms integrating visual, thermal, acoustic, and RF data
- Design and maintain data lakes, warehouses, and real-time streaming architectures
- Develop conversational AI interfaces using open-source LLMs such as Llama and Mistral
- Establish data quality standards, validation checks, and governance procedures throughout the data lifecycle
- Develop and execute robust testing and validation strategies for AI/ML models, including performance under degraded data conditions and adversarial scenarios
- Optimize AI workloads for embedded platforms like Jetson and Intel Neural Compute Stick
- Implement hardware acceleration techniques using CUDA and TensorRT
- Profile and optimize memory and power consumption for edge devices
- Support embedded systems teams with AI hardware integration and design distributed inference systems for degraded network environments
Benefits
- Opportunity to work on impactful projects that directly influence national security
- Collaborative environment with a small, elite team where contributions are immediately recognized
- Access to state-of-the-art hardware and technology platforms
- Rapid prototyping environment enabling deployment of ideas within weeks
- Direct interaction with end users and field deployments to see real-world impact
- Support for professional development, including conference attendance and training opportunities
- Flexible work arrangements, including remote work and occasional field exercises
- Chance to shape the future of tactical edge computing and AI applications
Equal Opportunity
MAG Aerospace is an Equal Opportunity/Affirmative Action Employer committed to diversity, equity, and inclusion. We encourage qualified candidates from all backgrounds 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. We provide accessible application processes and reasonable accommodations for individuals with disabilities in accordance with applicable laws.