Senior Data Scientist / AI Machine Learning Research Engineer

CACI International; Sterling (IL); On-site; USD 113,000 - 238,000; Full time

Job summary

CACI International is seeking a Senior AI and Machine Learning Research Engineer to apply machine learning and statistics to solve RF-domain problems. You will develop algorithms, build data pipelines, and deploy models in cloud environments, with a strong emphasis on reproducible research and governance.

The role requires a Master’s in a quantitative field with 7+ years of experience, deep ML knowledge, and active TS/SCI clearance with the ability to obtain SCI with Polygraph. U.S.

Qualifications

• Master’s degree in quantitative field with mathematical underpinning and 7+ years of experience.
• Experience developing ML models and pipelines across domains.
• Strong background in machine learning, mathematics, and statistics.
• Comfortable with Linux OS and common Linux utilities.

Responsibilities

• Develop and implement ML algorithms for RF domain problems.
• Design and build data pipelines (ETL, data warehousing) for large-scale data.
• Deploy ML solutions on cloud infrastructure with containerization and CI/CD.
• Code in Python and SQL, use Spark and Airflow for data processing.
• Establish ML governance: track datasets/models, reproduce research.

Skills

Machine learning

Statistics

Data analysis

Linux

Security clearance

Education

Master’s degree in quantitative field

Ph.D. in related field (desired)

Tools

Python

SQL

Spark

Airflow

TensorFlow

PyTorch

scikit-learn

AWS/Azure/GCP

Job description

Job Title: Senior Data Scientist / AI Machine Learning Research Engineer

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: Continental US

* * *

The Opportunity:
CACI has an exciting new opportunity for a Senior AI and Machine Learning Research Engineer. Apply machine learning, statistics, to develop algorithms to solve challenging problems, signal processing, and computer networking domains. In this role, you’ll leverage your strong foundation in machine learning, data science, and signal processing to solve complex challenges in the RF domain.

Responsibilities:

1. Strong mathematical foundation in statistics, linear algebra, and calculus with demonstrated ability to understand and implement machine learning algorithms from first principles rather than solely relying on pre-built libraries.

2. Proficiency in designing and building data pipelines, including experience with ETL processes, data warehousing solutions, and optimizing workflows for large-scale data processing.

3. Hands-on experience with cloud-based infrastructure (e.g., AWS, Azure, GCP) for deploying ML solutions, including containerization, orchestration, and CI/CD pipelines for model deployment.

4. Programming expertise in Python and SQL, with experience using data engineering frameworks (e.g., Spark, Airflow) and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).

5. Demonstrated experience in establishing ML governance practices, including version control for datasets and models, experiment tracking, model monitoring, and implementing reproducible research principles.

Qualifications:

Required:

• Master’s degree in quantitative field with mathematical underpinnings and at least 7 years’ experience.

• Experience developing models,.

• Strong background in machine learning, mathematics and statistics.

• Comfortable using Linux operating systems and commonly used Linux utilities.

• Must be a US Citizen with the ability to obtain, maintain and/or transfer the required security clearance as dictated by the contract

• Must have active Top Secret Clearance with the ability to obtain SCI with Polygraph

Desired:

• Ph.D. in computer science, computer engineering, or machine learning, Statistics, applied mathematics or Physics.

• Experience applying machine learning to signal processing and/or other time-series data analysis applications.

• Knowledge of or experience with information theory, probability theory, parametric and non‑parametric statistical tests.

• Familiarity with concepts and techniques associated with adversarial AI and AI/ML assurance.

• Active Top Secret/SCI clearance preferred.

What You Can Expect:

A culture of integrity.

At CACI, we place character and innovation at the center of everything we do. As a valued team member, you’ll be part of a high-performing group dedicated to our customer’s missions and driven by a higher purpose – to ensure the safety of our nation.

An environment of trust.

CACI values the unique contributions that every employee brings to our company and our customers - every day. You’ll have the autonomy to take the time you need through a unique flexible time off benefit and have access to robust learning resources to make your ambitions a reality.

A focus on continuous growth.

Together, we will advance our nation’s most critical missions, build on our lengthy track record of business success, and find opportunities to break new ground — in your career and in our legacy.

Pay Range :

There are a host of factors that can influence final salary including, but not limited to, geographic location, Federal Government contract labor categories and contract wage rates, relevant prior work experience, specific skills and competencies, education, and certifications. Our employees value the flexibility at CACI that allows them to balance quality work and their personal lives. We offer competitive compensation, benefits and learning and development opportunities. Our broad and competitive mix of benefits options is designed to support and protect employees and their families. At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.

The proposed salary range for this position is:

$113,200 - $237,800

CACI is anEqualOpportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, age, national origin, disability, status as a protected veteran, or any otherprotectedcharacteristic.