Join CACI’s Cyber Science and Technology Division to apply advanced algorithms and tackle complex optimization and dynamical systems challenges. You’ll research, develop, and implement innovative solutions using state-of-the-art methods-including machine learning-integrated into larger hardware and software systems. This role offers technical leadership, opportunities to present to customers, and involvement in business development.

Responsibilities

• Develop and justify performance of algorithms for optimization, signal processing, and dynamical systems

• Conduct detailed modeling and simulation, quantifying impacts of candidate solution architectures

• Oversee development of standalone applications and major software subsystems, ensuring adherence to software best practices

• Assist in creating detailed technical plans, including tasks, schedules, and labor estimates

• Develop automated tests to rigorously evaluate algorithms and software capabilities

• Contribute as a core team member during proposal development and project execution

Required Qualifications

• Master’s degree in computer science, applied mathematics, physics, or related discipline, plus at least 5 years’ experience

• Proven experience developing algorithms and software applications

• Strong background in optimization, signal processing, dynamical systems theory, and analysis of linear/nonlinear systems

• Significant experience with Python and C++

• Proficiency with Linux operating systems and utilities

• Experience with standard modeling and simulation software packages, tools, and methods

• Ability to anticipate strengths and weaknesses of algorithmic solutions; perform simulation, testing, and evaluation to compare alternatives quantitatively

• Effective communication skills for presenting research outcomes to senior staff and customers

• Demonstrated leadership in organizing and executing technical efforts

• US citizenship with ability to obtain, maintain, or transfer required security clearance

• Top Secret clearance

Desired Qualifications

• Ph.D. in computer science, applied mathematics, physics, or related discipline

• Experience integrating machine learning methods with signal processing and/or time-series data analysis

• Knowledge of information theory, probability theory, and statistical tests (parametric/non-parametric)

• Experience with data-driven approaches to systems analysis

• Top Secret with SCI 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: