Applied AI Researcher: Cyber-Physical Systems Lead

The Johns Hopkins University Applied Physics Laboratory; Laurel (MD); On-site; USD 100,000 - 245,000; Full time

Job summary

The Johns Hopkins University Applied Physics Laboratory (APL) seeks an Applied AI Researcher to address challenges for defense and intelligence communities. You will join the Cyber-Physical Systems Development Group to analyze and exploit technologies across cameras, drones, networks, and wearables, turning research into operational capabilities.

Responsibilities include leading small teams, architecting solutions, mentoring engineers, and collaborating with sponsors to define new research

Qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Computer Engineering, Electrical Engineering, or related field.
• 3+ years in software eng., cybersecurity, cyber-physical systems, or related fields.
• Strong programming in Python, C/C++, Rust, or similar; develop and deliver analytical tools.
• Experience applying ML, LLMs, or agentic AI to extract insights and automate investigations.
• Ability to independently define approaches, own problems, and drive to completion.

Responsibilities

• Develop software systems for cyber-physical capabilities against complex systems.
• Apply AI/ML to automate operations and enable intelligent decisions.
• Lead R&D efforts: architect solutions, manage multidisciplinary teams, transition to sponsors.
• Shape future cyber-physical ops by identifying technologies and new research directions.
• Mentor engineers and foster collaboration across teams.

Skills

Python

C/C++

Rust

ML/AI

communication

Education

Bachelor's degree in CS/AI/Engineering

Master's or PhD (advantage)

Job description

The Johns Hopkins University Applied Physics Laboratory (APL) seeks an Applied AI Researcher to address challenges for defense and intelligence communities. You will join the Cyber-Physical Systems Development Group to analyze and exploit technologies across cameras, drones, networks, and wearables, turning research into operational capabilities.

Responsibilities include leading small teams, architecting solutions, mentoring engineers, and collaborating with sponsors to define new research