AI Engineer

Markon•Annapolis Junction, MD

1d•Hybrid

About The Position

Markon’s partner company is seeking an experienced Artificial Intelligence (AI) Engineer to support the evolution of the RAD architecture . This is a transformative role focused on designing, prototyping, and integrating AI-driven capabilities that augment human intelligence, streamline workflows, and enhance the effectiveness of intelligence operations . The AI Engineer will work closely with system engineers, software developers, and mission stakeholders to bring advanced AI concepts from idea to operational reality for an IC customer. This position allows for up to two (2) days of telework , with the remainder onsite.

Requirements

Active TS/SCI w/ Polygraph
Proven experience designing and developing AI and machine learning solutions
Strong understanding of machine learning model development, training, and evaluation
Experience performing EDA on complex, real-world datasets
Ability to write and maintain production-quality code
Experience working in AWS cloud environments , including AI/ML services
Familiarity with MLOps practices and tools

Responsibilities

AI Design & Development Lead the design, development, and deployment of AI-driven solutions integrated into the existing RAD architecture
Prototype and evaluate new AI/ML models to address mission needs
Write production-quality code and maintain existing AI systems to ensure reliability, scalability, and performance
Collaboration & Technical Leadership Serve as a technical liaison across cross-functional teams, including system engineers, software developers, and domain experts
Clearly communicate recommended AI approaches, including tradeoffs, risks, and implementation considerations , to both technical and non-technical stakeholders
Support architecture and design discussions to ensure AI solutions align with system constraints and mission objectives
Data Analysis & Modeling Perform Exploratory Data Analysis (EDA) on structured and unstructured datasets
Identify data quality issues and inform data preparation and feature engineering strategies
Determine optimal data representations and input formats for AI and machine learning models
Model Development & Evaluation Develop, train, and evaluate a variety of machine learning and AI models
Implement robust testing, validation, and evaluation strategies to ensure accuracy, reliability, and fairness
Monitor model performance and support model tuning and optimization
Continuous Improvement & Innovation Stay current with emerging trends and advancements in AI, machine learning, and data science
Proactively identify opportunities to apply new techniques and technologies to improve existing systems and solve complex mission problems
Cloud & MLOps Support Leverage Amazon Web Services (AWS) to deploy and manage AI/ML solutions
Utilize MLOps tools and practices to support model deployment, monitoring, versioning, and lifecycle management at scale