AI/ML Engineer Lead

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,MLOpsworkflows, and automated analytics solutions for intelligence exploitation

• DevelopMulti-INTdata 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:

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

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

• Developandmaintaindata pipelines using ETL processes, API integration, and distributed computing frameworks

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

• ImplementMLOpsbest practices including model versioning, automated testing, continuous integration, and deployment automation

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

• Developdata visualization dashboards and interactive analytics tools for intelligence analysts and operators

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

• IntegrateAI/ML capabilities with intelligence data platforms and enterprise data fabrics

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

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

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

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

• Presentfindings and recommendations to technical teams and senior leadership

Qualifications:

Required:

• ActiveSecret security clearance (required)

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

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

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

• Demonstratedexperience developing and deploying machine learning models in production environments

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

• Strongunderstanding of statistical methods, probability theory, and mathematical modeling

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

• Knowledgeof SQL and NoSQL databases and experience with data querying and database design

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

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

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

• Demonstratedability 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, orrelated field

• Experiencewith intelligence community systems and intelligence data formats

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

• Experiencewith distributed computing frameworks such as Apache Spark, Hadoop, orDask

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

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

• Knowledgeof computer vision and image processing for geospatial or imagery intelligence

• ExperiencewithMLOpstools such asMLflow, Kubeflow, or similar platforms

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

• Experiencewith containerization technologies (Docker, Kubernetes) for model deployment

• Knowledgeof graph analytics and network analysis for intelligence applications

• Experiencewith time series analysis and forecasting methods

• Understandingof reinforcement learning and optimization algorithms

• Familiaritywith explainable AI (XAI) and model interpretability techniques

• ExperiencewithDevSecOpspractices and CI/CD pipelines for AI/ML deployments

• Knowledgeof adversarial machine learning and AI security considerations

• Previousexperience supporting government program offices in defense or intelligence sectors