AI & Autonomous Systems Engineer Intern — Shape Next-Gen Flight

The Johns Hopkins University Applied Physics Laboratory; Laurel (MD); On-site; USD 31,000 - 66,000; Full time

Job summary

The Johns Hopkins University Applied Physics Laboratory (APL) in Laurel, MD, invites motivated students for a 2027 Internship – AI and Autonomous Systems Engineer. You will work in a multidisciplinary team to advance autonomous systems, AI, and simulation across software, hardware, and flight platforms.

You’ll collaborate on prototype development, data workflows, and ML model deployment while building real-world capabilities for defense applications.

Qualifications

• Pursuing a Bachelor's, Master's, or PhD in a STEM field (Math, CS, Physics, Engineering).
• Experience with autonomous systems, AI, ML, robotics, data science, and basic modeling/simulation.
• Strong communication and teamwork; 3.0 GPA; ability to obtain Secret-level clearance by start date.

Responsibilities

• Join multi-disciplinary teams on software/hardware design, flight system test, and autonomous air platforms.
• Prototype and simulate AI/autonomous systems by coding, software development (simulation/visualization), and interfacing software/hardware.
• Contribute to data-to-deployment lifecycle of ML models and collaborate with expert engineers and scientists.

Skills

Autonomous systems

Artificial intelligence

Machine learning

Robotics

Data science

Statistics

Communication skills

Team collaboration

Education

Bachelor's, Master's, or PhD in STEM

Tools

Python

C++

C

C#

Java

Linux

JavaScript

Terminal

Bash

PyTorch

TensorFlow

Unity

MATLAB

Job description

The Johns Hopkins University Applied Physics Laboratory (APL) in Laurel, MD, invites motivated students for a 2027 Internship – AI and Autonomous Systems Engineer. You will work in a multidisciplinary team to advance autonomous systems, AI, and simulation across software, hardware, and flight platforms.

You’ll collaborate on prototype development, data workflows, and ML model deployment while building real-world capabilities for defense applications.