Autonomy Test and Evaluation Tools Software Engineer

The Johns Hopkins Applied Physics Laboratory (APL) is seeking an Autonomy Test and Evaluation Tools Software Engineer to develop simulation-based test and evaluation software for autonomous maritime platforms. This onsite role in Laurel, MD focuses on creating high-fidelity simulation environments, validating autonomy decision-making, and combining real-world field data with analytical evaluation in an agile prototyping setting.

Responsibilities

• Develop end-to-end software tools for simulation-based test and evaluation (T&T&E), including requirements definition, architecture, implementation, and validation.
• Design and build high-fidelity simulation environments to assess autonomy algorithms under both nominal and off-nominal conditions.
• Develop verification and validation approaches for decision-making systems, including handling edge cases and emergent behaviors.
• Use data science, statistics, and machine learning techniques to analyze performance and develop new evaluation methods.
• Plan and support field experiments, integrating real-world data with simulation-based analysis.
• Collaborate with multidisciplinary teams within an agile, rapid prototyping environment.

Required Qualifications

• BS in Software Engineering, Computer Science, or a related technical field such as Robotics, Physics, or Mathematics.
• 5+ years of professional experience in software development using Python and/or C++.
• Experience with full-lifecycle software development.
• Experience or interest in autonomous systems, robotics, simulation, or test and evaluation.
• Experience developing or working with simulation environments or modeling and simulation (M&S) tools.
• Strong organizational and planning skills, with a demonstrated ability to contribute effectively in team settings.
• Ability to communicate clearly in written and verbal formats.
• Ability to obtain an interim Secret-level security clearance by the start date and ultimately obtain a Top Secret clearance.

Technologies

• Python
• C++
• ROS
• Gazebo
• Unity

Preferred / Above-Minimum Qualifications

• MS or PhD in Software Engineering, Computer Science, Robotics, or a related technical field.
• Experience developing or evaluating autonomous systems, including decision-making, planning, or behavior-based autonomy.
• Experience with simulation-based test and evaluation or M&S environments.
• Experience with verification and validation (V&V) for complex or safety-critical systems.
• Experience developing machine learning approaches such as reinforcement learning, imitation learning, or online/offline learning.
• Experience integrating autonomy software into simulation frameworks (for example, ROS, Gazebo, Unity, or similar environments).
• Experience supporting or leading field testing of autonomous systems.
• Active Top Secret security clearance.

Location and Compensation

Location: Laurel, MD (onsite).
Compensation: USD 100,000 - 245,000 per year.

Benefits

• Robust education assistance program.
• Unparalleled retirement contributions.
• Healthy work/life balance.
• Comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development.
• Sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance.
• Annual salary will be prorated based on the number of hours worked for salaried employees scheduled to work less than 40 hours per week.