AI/ML Engineer Lead

CACI; Maryland; On-site; USD 140,000 - 190,000; Full time

Job summary

CACI is seeking an AI/ML Engineer Lead to drive advanced AI/ML engineering for DoD intelligence, EW, and cyber systems. You will design models, build pipelines, and shepherd ML initiatives from concept to production.

You will mentor data scientists, collaborate with systems engineers and stakeholders, and ensure secure, scalable AI/ML deployments across mission applications.

Qualifications

• Active Secret security clearance (required).
• 10+ years of professional experience in data science and AI/ML engineering.
• Strong programming skills in Python, R, or similar languages.
• Experience deploying ML models in production environments.
• Experience with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, Keras.
• Knowledge of SQL/NoSQL databases and data visualization tools.

Responsibilities

• Lead AI/ML engineering efforts for DoD intelligence, EW, and cyber systems.
• Develop and implement advanced AI/ML algorithms and predictive analytics.
• Architect AI/ML pipelines, MLOps workflows, and automated analytics.
• Develop Multi-INT data fusion, geospatial analytics, and automation.
• Lead integration of AI/ML into mission applications and systems.
• Provide technical leadership and mentorship to data teams.
• Interface with systems engineers, software developers, and government stakeholders.
• Present findings to technical teams and senior leadership.

Skills

Python

R

ML frameworks

TensorFlow

PyTorch

Scikit-learn

Keras

Pandas

NumPy

SQL

NoSQL

ETL

Data Visualization

Spark

Hadoop

Education

Master's degree in CS/DS/Math/Stats/Eng

Tools

TensorFlow

PyTorch

Scikit-learn

Keras

Pandas

NumPy

SciPy

Tableau

SQL

NoSQL

Job description

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 int