U.S. Citizenship with ability to pass background investigation
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field
5+ years of experience in ML frameworks and production data pipelines
Experience developing and deploying ML solutions in public cloud environments
Proficiency with ML frameworks like TensorFlow, PyTorch, and scikit-learn
Strong programming skills in Python, with some knowledge of Java or R
Solid understanding of data structures, data modeling, and software architecture
Responsibilities
Design, develop, and deploy machine learning models and data pipelines
Import, process, and analyze large-scale data sets
Develop predictive models and conduct root cause and trend analyses
Build and optimize end-to-end data analytics solutions
Write, test, and maintain application code and ML models
Collaborate within a cross-functional Agile team for application development
Leverage cloud-based architectures for ML model deployment
Benefits
Comprehensive healthcare and wellness programs
Retirement savings plan with employer match
Flexible working environment with opportunities for remote work
Professional development and certification reimbursement
Opportunities for career advancement within a growth-focused organization
Full Job Description
Job Description:
Job Summary
We are seeking a motivated and experienced Mid-Level Data Engineer and Machine Learning (ML) Developer with Agile methodology experience to support advanced data analytics and machine learning initiatives. This role focuses on designing, developing, and deploying scalable ML models and data pipelines that solve complex, real-world problems. The ideal candidate is a strong problem solver who thrives in a collaborative, fast-paced environment and can work end-to-end across data engineering and machine learning workflows.
Responsibilities
Design, develop, and deploy machine learning models and data pipelines to support operational analytics and predictive insights.
Import, process, and analyze large-scale operational and performance datasets.
Develop predictive models, perform root cause analysis, trend analysis, and IoT signal analytics.
Build and optimize end-to-end data analytics solutions, from ingestion to model deployment.
Deliver ML software components in collaboration with Product and Data Science teams.
Write, test, and maintain application code and ML models, including automated testing and deployment.
Collaborate within a cross-functional Agile team to develop next-generation big data and ML applications.
Leverage cloud-based architectures to deploy scalable and optimized ML models.
Construct and maintain optimized data pipelines to feed ML models.
Use programming languages such as Python, Scala, or Java.
Apply CI/CD best practices, including test automation and monitoring.
Advocate for software and ML engineering best practices across the team.
Serve as a technical lead for large-scale initiatives when required.
Perform statistical analysis, model tuning, and performance evaluation.
Transform data science prototypes into production-ready solutions.
Build data visualization, manipulation, and processing tools for team use.
Ensure high-quality data, reproducible experiments, and actionable analytical outcomes.
Work with development teams to automate data logging and repeatable analytics tasks.
Qualifications
Required
U.S. Citizenship with the ability to pass a background investigation.
Applicable combination of education and experience:
Mid-Level (T3): Bachelors degree in Computer Science, Engineering, Mathematics, or related field, plus 5+ years of experience working with ML frameworks and production data pipelines.
Senior-Level (T4): Bachelors degree in a related field, plus 7+ years of experience, including 5+ years in data preparation and ML model development.
Proven experience as a Machine Learning Engineer, Data Engineer, or similar role.
Experience developing and deploying ML solutions in public cloud environments.
Proficiency with ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, Pandas, and similar tools.
Strong programming skills in Python, with working knowledge of Java or R.
Solid understanding of data structures, data modeling, and software architecture.
Strong background in mathematics, probability, statistics, and algorithms.
Experience developing and evaluating predictive models using large, high-volume datasets.
Knowledge of statistical techniques such as regression, classification, clustering, hypothesis testing, and optimization.
Ability to analyze relational data models and integrate ML model inputs/outputs into transactional systems.
Self-starter with the ability to work independently and collaboratively.
Strong organizational, time management, and communication skills.
Ability to work effectively in a fast-paced, dynamic environment.
Desired
Experience with Spark, Kafka, TensorFlow, PyTorch, or similar big data tools.
Experience building real-time or near real-time ML systems.
Prior experience leading or mentoring small technical teams.
Experience automating business processes using RPA technologies.
Familiarity with operational or enterprise-scale systems.
Working Place:
Virginia, Virginia, United States
Company :
2026 Feb 26th CyberSecurity - CACI International
About CACI International
CACI International Inc is a multinational professional services and information technology company. It provides services to many branches of the federal government including defense, homeland security, intelligence, and healthcare. CACI has approximately 23,000 employees worldwide. The company's mission is to provide enterprise and mission technology services and solutions that best fit the needs of its customers. CACI has been named a Fortune World's Most Admired Company, a Washington Post Top Workplace, and a Forbes Best Employer for Diversity.
