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# Software Engineer Asc - Early Career

- **Company:** Lockheed Martin
- **Location:** Fort Worth, TX, United States
- **Salary:** $67,000.0 - $124,400.0
- **Contract:** Permanent contract
- **Skills:** Microsoft Windows, Artificial Intelligence, Application Frameworks, C Sharp (Programming Language), C++ (Programming Language), Convex Optimization, Linux, Embedded Software, Statistical Hypothesis Testing, Python (Programming Language), Linear Programming, MATLAB, Machine Learning, NumPy, Object-Oriented Software Development, Real-Time Operating Systems, Tensorflow, State Estimation, SciPy, Sensor Fusion, Signal Processing, Simulink, Rust (Programming Language), Gaussian, Information Technology, Lidar, Programming Languages
- **Published:** October 22, 2026
- **Apply:** https://dejobs.org/x/x/EEF40DB77E0340618CF6BF2C60135F20/job/

## About the Role

Programming Languages: Proficiency in languages such as Python, C++, C#, or MATLAB.

Software Frameworks: Familiarity with software frameworks, such as NumPy, SciPy, or TensorFlow, MATLAB, MATLAB Object Oriented, for numerical computations.

Simulation Tools: Knowledge of simulation tools, such as Simulink or MATLAB, for modeling and testing sensor fusion systems.

Mathematical Foundations

Linear Algebra: Understanding of vector spaces, linear transformations, and matrix operations.

Probability Theory and Statistics: Familiarity with probability distributions, Bayes' theorem, and stochastic processes. Knowledge of statistical inference, estimation, and hypothesis testing.

Advanced topics: Understanding of numerical optimization, convex optimization, non-linear optimization, machine learning, and/or mathematical methods.

Signal Processing and Filtering

Signal Processing: Understanding of signal processing techniques, such as filtering, convolution, and Fourier analysis.

Kalman Filter: Familiarity with the Kalman filter algorithm, its variants (e.g., Extended Kalman Filter, Unscented Kalman Filter), and applications.

Particle Filter: Knowledge of particle filter algorithms and their applications in non-linear, non-Gaussian systems.

Tracking

Embedded Development: Acute proficiency in Programming Fundamentals applied to embedded systems.

Sensor Modeling: Understanding of sensor characteristics, noise models, calibration techniques, Signal Processing and Filtering, and Mathematical Foundations.

Data Association: Familiarity with data association techniques, such as nearest neighbor, joint probabilistic data association, and multiple hypothesis tracking.

State Estimation: Knowledge of state estimation algorithms, including Kalman filters, particle filters, and Bayesian estimation methods.

Sensor Integration and Management

Resource Allocation: Experience tasking, prioritizing, and scheduling of sensors and maximizing information value, system needs, or target tracking accuracy with a deep understanding of Programming Fundamentals.

Sensor Integration: Experience with integrating sensors like LIDAR, RADAR, or cameras and offboard sources., Bachelor's or Master's degree in Computer Science, Electrical Engineering, Mathematics, Aerospace Engineering, Mechanical Engineering or a related field

-- Experience with C++, C#, Rust, MATLAB, and/or Python

-- Real Time Operating System (RTOS) experience - (Windows & Linux)

-- Strong problem-solving, communication, and collaboration skills to work effectively with cross-functional teams

Desired Skills

-- Project experience in sensor fusion sub-domain(s) (e.g. state estimation, identification, correlation, sensor tasking) or coursework across domains including signal processing, artificial intelligence, autonomy/perception, artificial intelligence, navigation, or control systems in a sensor/systems application.

-- Experience implementing Artificial Intelligence, Machine Learning, or statistical algorithms in real time operating systems

-- Strong understanding of Object Oriented Programming (OOP)/Object Oriented Design (OOD)

-- Strong mathematical foundation in Linear Algebra, Probability Theory, and Statistics