Autonomy Simulation Engineer - T&E Specialist

Johns Hopkins Applied Physics Laboratory (APL); Laurel (NE); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

education assistance

strong retirement contributions

a healthy work/life balance

retirement plans

paid time off

medical

dental

vision

life insurance

disability coverage

flexible spending accounts

training and development

Job summary

Johns Hopkins University Applied Physics Laboratory (APL) is seeking a software professional to advance autonomous systems simulation and evaluation. The role covers requirements, architecture, implementation and validation of tools for simulation-based testing.

You will design high‑fidelity environments to assess autonomy algorithms, verify decision‑making systems, and apply data science to performance analysis.

Qualifications

• Bachelor's degree in software/CS or related field.
• 5+ years of professional software development experience.
• Interest in autonomous systems or robotics and simulation.

Responsibilities

• Develop software tools for simulation-based test and evaluation of autonomous systems.
• Design high-fidelity simulation environments for autonomy algorithms.
• Create methods to verify/develop decision-making systems and edge cases.
• Apply data science, statistics and ML to analyze performance.
• Plan and support field experiments integrating real data with simulations.
• Collaborate with multidisciplinary teams in an agile, rapid-prototyping setting.

Skills

5+ years software development

Python/C++

Team collaboration

Clear communication

Education

Bachelor's degree in Software Eng/CS or related

Masters or PhD preferred

Tools

ROS

Gazebo

Unity

Modeling/simulation tools

Job description

Johns Hopkins University Applied Physics Laboratory (APL) is seeking a software professional to advance autonomous systems simulation and evaluation. The role covers requirements, architecture, implementation and validation of tools for simulation-based testing.

You will design high‑fidelity environments to assess autonomy algorithms, verify decision‑making systems, and apply data science to performance analysis.