General Atomics Integrated Intelligence, Inc. (GA-Intelligence), an affiliate of General Atomics, was founded in 1989 and is located in Charlottesville, VA. It provides custom software development and innovative information engineering solutions to customers in government and private industry.

We build mission-critical software and analytics for defense and intelligence customers operating in complex, data-rich, and high-consequence environments. Our teams solve hard technical problems across tracking, sensor fusion, geospatial analytics, and large-scale operational software. We value rigorous thinking, sound technical judgment, and practical execution.

This is an environment for people who want their work to matter. Our teams partner closely across mathematics, software engineering, systems engineering, and mission domains to build capabilities that are used in the real world. We offer the opportunity to work on technically demanding problems with strong teammates in an organization that cares about both innovation and operational impact.

We are seeking an Applied Mathematician to help develop advanced tracking algorithms (for tracking moving objects using sensors) for mission-critical applications. This role is ideal for someone with deep mathematical training, strong programming ability, and a desire to apply rigorous analytical thinking to difficult real-world problems involving uncertain, incomplete, ambiguous, and dynamic data.

You will work with engineers, tracking specialists, and technical leaders to design, evaluate, and improve algorithms for detecting, associating, and maintaining tracks across large volumes of sensor and contextual data. The right candidate will be comfortable moving between mathematical analysis, algorithm design, simulation, experimentation, and software implementation.

This is a hands-on technical role for someone who enjoys turning theory into operational capability.

• Develop and improve algorithms for multi-object tracking, data association, track initiation, track maintenance, and track quality assessment.
• Apply advanced mathematical and statistical methods to problems involving noisy, incomplete, ambiguous, and time-varying data.
• Design, prototype, implement, and evaluate tracking approaches in software.
• Analyze tracker performance and propose improvements to accuracy, robustness, scalability, and computational efficiency.
• Build simulation, test, and evaluation methods to characterize algorithm behavior across a range of operational conditions.
• Work closely with software engineers to transition algorithms from prototype to production-quality implementations.
• Collaborate with domain experts, system engineers, and technical leadership to translate mission needs into sound technical approaches.
• Contribute to technical documentation, design reviews, test events, and customer-facing discussions as needed.
• Support integration of tracking methods into larger analytic, fusion, and operational software systems.

Job Qualifications

• Typically requires a bachelor's degree, master's degree or PhD in data science, applied mathematics, statistics, computer science, or related technical/quantitative discipline from an accredited institution and progressive data science experience as follows; five or more years of experience with a bachelor's degree, three or more years of experience with a master's degree, or one or more years with a PhD. May substitute equivalent experience in lieu of education.
• Strong foundation in probability and statistics, stochastic processes, estimation theory, optimization, and linear algebra.
• Programming experience in one or more languages such as Python, C , Java, Matlab, or similar.
• Experience developing, implementing, or evaluating mathematical algorithms in code.
• Ability to work independently on technically complex problems and communicate results clearly.
• Ability to obtain and maintain DoD security clearance is required.

• Experience with multi-object tracking, target tracking, sensor fusion, or related estimation problems.
• Familiarity with Kalman filtering, nonlinear filtering, Bayesian estimation, probabilistic data association, multiple hypothesis tracking, random finite set methods, or track fusion.
• Experience working with real-world sensor data and imperfect operational data sets.
• Experience with algorithm performance analysis, Monte Carlo methods, and statistical evaluation.
• Familiarity with collaborative software development practices, including testing, version control, and code reviews.

Job Category

Engineering

Experience Level

Mid-Level (3-7 years)

Workstyle

Hybrid

Full-Time/Part-Time

Full-Time Salary

Pay Range Low

98,100

Pay Range High

171,398

Travel Percentage Required

0% - 25%

Relocation Assistance Provided?

Yes

US Citizenship Required?

Yes

Clearance Required?

Yes

Clearance Level

Top Secret (SCI access eligible)