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2027 Low Observables Engineer Intern

Anduril Industries
Costa Mesa, USA
Intern
Onsite
Discovered 4 days ago
matlabpythonsolidworks

Full Job Posting

REQUIRED QUALIFICATIONS

  • Must be pursuing a bachelor’s or master’s degree in Electrical Engineering, Aerospace Engineering, Mechanical Engineering, or a related field.
  • Must be returning to school at the end of the internship to continue academic studies for at least one quarter or semester.
  • Must be a U.S. Person due to required access to U.S. export-controlled information or facilities; U.S. clearance eligibility may be required depending on program.
  • Ability to complete an in-person 12-week internship in one of our offices in summer 2027.

PREFERRED QUALIFICATIONS:

  • Coursework in at least one of: electromagnetics or RF, aircraft or vehicle design, or materials and manufacturing processes
  • Working knowledge of a scripting or analysis language such as MATLAB, Python, or C++
  • Familiarity with a 3D CAD package such as NX, CATIA, SolidWorks, or Creo
  • Demonstrated hands-on engineering work: a capstone or senior design project, internship, undergraduate research, or a student competition team
  • Ability to explain a technical result clearly, in writing and in a design review
  • Exposure to any electromagnetic simulation tool, such as HFSS, CST, FEKO, or COMSOL. X-Patch, SENTRi, and McMoM2D are government codes and we do not expect you to have used them
  • Coursework or project experience with composites, additive manufacturing, casting, or injection molding
  • Experience with laboratory RF measurement: network analyzers, anechoic chambers, or antenna pattern measurement
  • Experience reducing, visualizing, and sanity-checking measured data sets
  • A prior internship or co-op in aerospace, defense, or another hardware-heavy environment
  • US Hourly Range $34—$50 USD
  • The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:

Benefits

  • At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits.

Protecting Yourself from Recruitment Scams

Anduril is committed to maintaining the integrity of our Talent acquisition process and the security of our candidates. We've observed a rise in sophisticated phishing and fraudulent schemes where individuals impersonate Anduril representatives, luring job seekers with false interviews or job offers. These scammers often attempt to extract payment or sensitive personal information.

To ensure your safety and help you navigate your job search with confidence, please keep the following critical points in mind:

No Financial Requests: Anduril will never solicit payment or demand personal financial details (such as banking information, credit card numbers, or social security numbers) at any stage of our hiring process. Our legitimate recruitment is entirely free for candidates.

Please always verify communications:

Direct from Anduril: If you receive an email from one of our recruiters, it will only come from an @anduril.com address.

Via Agency Partner: If contacted by a recruiting agency for an Anduril role, their email will clearly identify their agency. If you suspect any suspicious activity, please verify the agency's authenticity by reaching out to [email protected].

Exercise Caution with Unsolicited Outreach: If you receive any communication that appears suspicious, contains grammatical errors, or makes unusual requests, do not engage. Always confirm the sender's email domain is @anduril.com before providing any personal information or clicking on links.

What to Do If You Suspect Fraud: Should you encounter any questionable or fraudulent outreach claiming to be from Anduril, please report it immediately to [email protected]. Your proactive caution is invaluable in protecting your personal information and upholding the security and trustworthiness of our recruitment efforts.

Data Privacy

To view Anduril's candidate data privacy policy, please visit https://anduril.com/applicant-privacy-notice/.

By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening and assessing potential risks as part of your application process. This third-party service provider provides risk-intelligence services that may include analysis of sanctions and watchlists, adverse media, public-record information, and other lawful open-source or commercial data sources. This third-party service provider does not act as a consumer reporting agency. Use of this provider helps to ensure compliance with applicable laws and protect technology, intellectual property, and organizational security.

Responsibilities

  • Run broadband Radar Cross Section (RCS) analysis on components and full air vehicles, and learn to judge when a prediction can be trusted
  • Support the design and development of Low Observable unmanned air systems, from early configuration trades through detailed design
  • Build and improve the analysis tools, scripts, and validation workflows the team runs on
  • Model LO materials and treatments, and help select and optimize them for specific components
  • Support manufacturing and validation planning, including tolerances, inspection methods, and what is actually producible at rate
  • Help plan and execute RCS measurement campaigns in indoor chambers and on outdoor ranges, then reduce and interpret the data
  • Compare measured results against predictions, chase down the disagreements, and feed what you learn back into the models

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