AI/ML Engineer Lead

Job Title: AI/ML Engineer Lead Job Category: Science Time Type: Full time Minimum Clearance Required to Start: TS/SCI Employee Type: Regular Percentage of Travel Required: Up to 10% Type of Travel: Local * * * The Opportunity: 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   Relevant   industry certifications such as AWS Certified Machine Learning Specialty, Google Professional Machine Learning Engineer, or Microsoft Certified: Azure AI Engineer   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