Vital Lyfe

Vital Lyfe

Electrical Engineering Internship - Fall 2026

Los Angeles - Greater Area · Intern · Internship

Sponsorship not specifiedDetected 13 days ago
MATLABAltiumElectrical EngineeringCommunicationProblem SolvingMentoringThermodynamics

About the role

  • About Vital Lyfe Vital Lyfe is a tech company redefining water autonomy through innovation, creating a new category of personal water-making technology built to scale where infrastructure can't.
  • Attributes: - A passion for solving real-world problems. - Strong analytical and problem-solving skills. - Excellent communication and teamwork abilities.

Responsibilities

  • Work on developing and optimizing the electrical components of our desalination devices.
  • Utilize tools like Altium, MATLAB, or similar platforms for design and simulation.

Requirements

  • Currently pursuing a degree in Electrical Engineering.

Skills

  • Attributes:
  • A passion for solving real-world problems.
  • Strong analytical and problem-solving skills.
  • Excellent communication and teamwork abilities.
  • Why Join Us?
  • Impact: Work on technology that addresses one of humanity's most pressing challenges.
  • Hands-On Experience: Tackle real-world projects and gain invaluable industry knowledge.
  • Growth Opportunities: Contribute to a growing startup and help shape its future.
  • Location Requirement: Ability to work 100% onsite in Torrance, CA (remote or hybrid work will not be considered)
  • Vital Lyfe is an Equal Opportunity Employer

Benefits

  • Education: Currently pursuing a degree in Electrical Engineering.

Company info

  • About Vital Lyfe
  • Vital Lyfe is a tech company redefining water autonomy through innovation, creating a new category of personal water-making technology built to scale where infrastructure can't.
  • We're looking for passionate and driven interns to join our mission and gain hands-on experience working on impactful projects.
  • What We're Looking For

This listing is sourced directly from Vital Lyfe's careers page and normalized into a canonical job model.