Lead artificial intelligence and machine learning engineering efforts for Department of Defense intelligence, electronic warfare, and cyber systems. As an AI/ML Engineer Lead, you will: 

• Develop and implement advanced AI/ML algorithms, predictive analytics, and decision support capabilities for intelligence and mission systems 

• Lead data science initiatives including data mining, statistical modeling, and machine learning to extract insights from large structured and unstructured datasets 

• Architect and implement AI/ML pipelines, MLOps workflows, and automated analytics solutions for intelligence exploitation 

• Develop Multi-INT data fusion capabilities, geospatial analytics, and intelligence processing automation 

• Lead the integration of AI/ML capabilities into mission applications and operational systems 

• Provide technical leadership and mentorship to data science and AI/ML engineering teams 

• Interface with systems engineers, software developers, and government stakeholders on AI/ML architecture and implementation 

Responsibilities: 

• Design and develop machine learning models using supervised and unsupervised learning techniques for intelligence analysis and automation 

• Implement natural language processing (NLP), computer vision, and deep learning solutions for intelligence data exploitation 

• Develop and maintain data pipelines using ETL processes, API integration, and distributed computing frameworks 

• Build predictive analytics models and decision support tools to enhance intelligence operations and mission effectiveness 

• Implement MLOps best practices including model versioning, automated testing, continuous integration, and deployment automation 

• Apply statistical methods, graph algorithms, and advanced analytics to support intelligence objectives 

• Develop data visualization dashboards and interactive analytics tools for intelligence analysts and operators 

• Work with large-scale data architectures including SQL and NoSQL databases, data lakes, and cloud-based analytics platforms 

• Integrate AI/ML capabilities with intelligence data platforms and enterprise data fabrics 

• Conduct exploratory data analysis, feature engineering, and model validation to ensure accuracy and performance 

• Develop technical documentation including model specifications, data science methodologies, and performance metrics 

• Collaborate with cybersecurity teams to ensure secure AI/ML implementations and protect against adversarial attacks 

• Research emerging AI/ML technologies and recommend innovative solutions for intelligence modernization 

• Present findings and recommendations to technical teams and senior leadership 

Qualifications: 

Required:  

• Active Secret security clearance (required) 

• Master's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or related quantitative field 

• 10+ years of professional experience with data science and AI/ML engineering 

• Strong programming skills in Python, R, or similar languages commonly used in data science applications 

• Demonstrated experience developing and deploying machine learning models in production environments 

• Experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, Keras, or similar platforms 

• Strong understanding of statistical methods, probability theory, and mathematical modeling 

• Experience with data manipulation and analysis using tools such as Pandas, NumPy, and SciPy 

• Knowledge of SQL and NoSQL databases and experience with data querying and database design 

• Experience with data visualization tools and techniques using tools such as Matplotlib, Seaborn, Tableau, or similar platforms 

• Strong analytical and problem-solving skills with ability to extract insights from complex datasets 

• Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders 

• Demonstrated ability to lead technical teams and mentor junior data scientists 

Desired:  

• Active Top Secret clearance with SCI eligibility  

• Ph.D. in Data Science, Computer Science, Mathematics, Statistics, or related field 

• Experience with intelligence community systems and intelligence data formats 

• Knowledge of SIGINT, GEOINT, or Multi-INT data processing and analytics 

• Experience with distributed computing frameworks such as Apache Spark, Hadoop, or Dask 

• Familiarity with deep learning architectures including CNNs, RNNs, LSTMs, and Transformer models 

• Experience with natural language processing (NLP) and text analytics for intelligence documents 

• Knowledge of computer vision and image processing for geospatial or imagery intelligence 

• Experience with MLOps tools such as MLflow, Kubeflow, or similar platforms 

• Understanding of cloud platforms such as AWS, Azure, or on-premises cloud solutions for AI/ML workloads 

• Experience with containerization technologies (Docker, Kubernetes) for model deployment 

• Knowledge of graph analytics and network analysis for intelligence applications 

• Experience with time series analysis and forecasting methods 

• Understanding of reinforcement learning and optimization algorithms 

• Familiarity with explainable AI (XAI) and model interpretability techniques 

• Experience with DevSecOps practices and CI/CD pipelines for AI/ML deployments 

• Knowledge of adversarial machine learning and AI security considerations 

• Previous experience supporting government program offices in defense or intelligence sectors