Human-Machine Systems Engineer Intern

Johns Hopkins Applied Physics Laboratory; Laurel (MD); Presencial; USD 31 000 - 66 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Education assistance

Retirement contributions

Work-life balance

Resumo da oferta

Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, is seeking a proactive Human‑Machine Engineering team member to design, prototype, and implement mission‑critical systems where humans and machines collaborate.

You will build robust systems engineering foundations and help reshape warfighter‑oriented capabilities, partnering with algorithm developers, computer scientists, and human factors engineers.

Qualificações

• Pursuing degree in Human Factors, UX/UI, Civil Engineering, Industrial Engineering, Systems Engineering, Computer Science, Software Engineering, Web Development, Game Development, HCI, or related field with min 3.0 GPA.
• Ability to work independently and with teams.
• Excellent oral and written communication skills.
• Citizenship and potential for Secret clearance.

Responsabilidades

• Contribute to design and development of next-generation mission-critical systems.
• Prototype solutions and perform systems engineering to enable these systems.
• Communicate and collaborate across teams to shape the vision for our country’s future.

Conhecimentos

Human Factors

UX/UI

Systems Engineering

Data Visualization

Wireframing

Prototyping

Web Development

Unity

Python

C++

JavaScript

Formação académica

Bachelor’s degree or higher

Ferramentas

Unity

Python

C++

Java

JavaScript

HTML

CSS/Sass/Less

React

Redux

Angular

Vue

Git

Confluence

JIRA

SQL

MongoDB

Docker

Descrição da oferta de emprego

Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, is seeking a proactive Human‑Machine Engineering team member to design, prototype, and implement mission‑critical systems where humans and machines collaborate.

You will build robust systems engineering foundations and help reshape warfighter‑oriented capabilities, partnering with algorithm developers, computer scientists, and human factors engineers.