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

* * *

• 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

• 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 No
  
  SQL 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

• 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 Tensor Flow, 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, Num Py, and Sci Py
• Knowledge of SQL and No
  
  SQL 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

• 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,…