Guidance, Navigation, and Controls Engineering Intern, Summer 2027

Posted 3 Days Ago
Be an Early Applicant
Palo Alto, CA, USA
In-Office
128K-135K Annually
Internship
eCommerce • Internet of Things • On-Demand • Transportation
Wing is an on-demand drone delivery service and platforms company.
The Role
Paid 12-week GNC software engineering internship developing motion planning, state estimation, and flight control algorithms for autonomous delivery aircraft. Interns will prototype robot behaviors, deploy and validate software in simulated and real environments, analyze flight data, and collaborate across perception, machine learning, simulation, aerodynamics, propulsion, and embedded software teams.
Summary Generated by Built In

About Wing: 

Wing offers drone delivery as a safe, fast, and sustainable solution for last mile logistics. Consumer appetites for on-demand services are increasing, but current delivery methods are inefficient, costly, and contribute to road accidents and air pollution. Wing’s fleet of highly automated delivery drones can transport small packages directly from businesses to homes on-demand, in minutes. We design, build, and operate our aircraft, and offer drone delivery services on two continents. Our technology is designed to be easy to integrate into existing delivery and logistics networks, offering a scalable drone delivery solution for a broad range of businesses. Wing is a part of Google's parent company, Alphabet, and our mission is to create the preferred means of delivery for the planet. If you're ready to do the greatest work of your life, come join us.

About the Program: 

Join Wing's 12-week paid summer internship! This is a hybrid, in-person program based in Palo Alto, CA, with start dates in May or June. Eligible candidates must be a current student enrolled in a degree program and intend to return to the program after the completion of the summer internship. 

About the Role:

Wing is looking for a GNC Software Engineering Intern to join our Guidance, Navigation, and Control team based in Palo Alto, CA. 

The GN&C team designs and implements algorithms for motion planning, state estimation, flight control, actuation, and contingency management. This position seeks motivated engineers who enjoy working on autonomous aerial robots. The successful candidate is able to demonstrate an ability to write and deploy software for motion planning, state estimation, or low-level control on real physical systems. This might include Model Predictive Control (MPC), trajectory optimization, Simultaneous Localization and Mapping (SLAM), Kalman Filtering, geometric control, computer vision, Vision-Language-Action (VLA) models, or related techniques. We’re looking for candidates with an understanding of both classical and state-of-the-art approaches to problems in robot control and autonomy, particularly in safety-critical applications.


In this role you will: 

  • Prototype new robot behaviors to solve important business problems
  • Develop and implement motion planning, state estimation, or control algorithms for Wing aircraft
  • Deploy and validate software in both simulated and real environments
  • Analyze flight data to determine the effectiveness of different approaches at scale
  • Work closely with other engineers in perception and computer vision, machine learning, simulation, aerodynamics and propulsion, and embedded software
  • Learn what it takes to build and maintain an autonomous system that has supported over 1 million deliveries for customers

What You’ll Need: 

  • Currently pursuing a Bachelor's, Master's, or doctoral degree in Robotics, Aerospace Engineering, Computer Science, or related field, graduating between December 2027 and August 2028
  • Strong examples of hands-on engineering experience from student project teams, research labs, internships, or other work experience
  • Coursework in linear algebra, optimization, machine learning, or statistics
  • Theoretical foundations in data structures and algorithms
  • Proficiency in C++ or Python

The US base salary range for this internship position is the salary range below + benefits. Wing’s salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your location during the hiring process.

Salary Range
$128,000—$135,000 USD

Wing is an equal opportunity employer and it is Wing's policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. Employment at Wing is based solely on a person's merit and qualifications directly related to professional competence. Wing does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.

If you have a need that requires accommodation during the interview process due to a disability or special need, please let us know by completing our Candidate Accommodations Request Form.

Skills Required

  • Currently pursuing a Bachelor's, Master's, or doctoral degree in Robotics, Aerospace Engineering, Computer Science, or a related field
  • Expected graduation between December 2027 and August 2028
  • Current enrollment in a degree program with intent to return after the internship
  • Strong hands-on engineering experience from student project teams, research labs, internships, or other work experience
  • Coursework in linear algebra, optimization, machine learning, or statistics
  • Theoretical foundations in data structures and algorithms
  • Proficiency in C++ or Python
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The Company
HQ: New York, NY
Year Founded: 2018

What We Do

Wing is reshaping the future of delivery. We are an on-demand drone delivery service that can deliver food, medicine or other items within minutes. We’ve also developed an unmanned traffic management platform to safely route drones through the sky. Our service is faster, safer and produces far less pollution than traditional delivery.

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