Autonomy Test and Evaluation Tools Software Engineer

Johns Hopkins Applied Physics Laboratory (APL) is seeking an Autonomy Test and Evaluation Tools Software Engineer to help build simulation-based test and evaluation software for autonomous maritime platforms. This role focuses on creating high-fidelity simulation environments, verifying and validating autonomy decision-making, and connecting real-world field data with analysis in an agile prototyping workflow.

What you’ll do

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

Basic 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, including a track record of contributing effectively in team settings.
• Ability to communicate clearly in both written and verbal formats.
• Ability to obtain an interim Secret-level security clearance by your start date and ultimately obtain a Top Secret clearance.

Technologies you may work with

• Python, C++, ROS, Gazebo, Unity

Compensation and location

• Location: Laurel, MD (onsite)
• Salary range: USD 100,000 - 245,000 per year
• Annual salary note: Annual salary will be prorated based on the number of hours worked for salaried employees scheduled to work less than 40 hours per week.

Benefits

• 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.
• Robust education assistance program.
• Unparalleled retirement contributions.
• Healthy work/life balance.
• Sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance.

Considered a plus

• 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 in simulation-based test and evaluation or M&S environments.
• Experience with verification and validation (V&V) of 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 (e.g., ROS, Gazebo, Unity, or similar environments).
• Experience supporting or leading field testing of autonomous systems.
• Active Top Secret security clearance.