Spacecraft Engineer Intern (Flight Software)

Oligo is building a manufacturing-in-the-loop foundation model to automate spacecraft design and production worldwide. Our approach allows customers to focus entirely on their own technology and mission objectives, while we handle everything, from design and manufacturing to launch and operations. Leveraging cutting edge AI-driven generative design and automated manufacturing, our ex-MIT, Harvard, and NASA JPL team work to create the most advanced payload-specific spacecraft at scale in weeks over months.
With world‑class advisors on our board, and fresh funding from top investors like Lux Capital, we’re always on the lookout for exceptional builders, fast learners, and ambitious engineers. Whether your passion lies in spacecraft systems, avionics, ML/AI, or advanced manufacturing, you’ll be collaborating across disciplines on real missions that fly, perform in orbit, and scale internationally.
We pair world-class AI/ML talent with top-tier satellite engineers under one roof to reimagine how space systems are built, starting from first principles. No bureaucracy. No legacy thinking.
If you think you’re a fit, we are extremely excited to meet you.

Are you obsessed with the intersection of code and hardware? Do you want to see your algorithms execute in orbit? Do you thrive on solving complex problems in real-time, high-reliability environments? Join our team as a Spacecraft Engineer Intern and help us build the foundational software for our next generation of spacecraft.

Play a pivotal role in designing, developing, and deploying the critical software that enables our spacecraft to perform their missions. If you're an expert in F-prime, real-time operating systems, and building robust embedded solutions, we want to talk to you!

As a Spacecraft Engineer Intern, you'll assist in the development, testing, and deployment of our spacecraft’s FSW stack. You will work closely with senior mentors to support:

• Flight Software: Design and implement flight software components within NASA/JPL’s open-source F-prime framework, focusing on resource-constrained embedded systems.

• Hardware Interfaces: Write and debug software that talks directly to hardware (sensors, actuators, radios) across protocols like I2C, SPI, UART, and Ethernet.

• Build Systems: Help maintain and extend our CMake build systems to ensure a smooth development pipeline.

• Verification & Testing: Develop unit tests and support Hardware-in-the-Loop (HITL) testing to ensure our code survives the harsh environment of space.

• Documentation: Assist in authoring Interface Control Documents (ICDs) and technical design notes, essential for mission success.

• Collaborate: Work across disciplines with Avionics and Mission Ops to troubleshoot complex hardware/software interactions.

• Optional: Researching, prototyping, and integrating Machine Learning (ML) and Artificial Intelligence (AI) algorithms into flight software, optimizing for real-time performance and resource efficiency.

• Academic Path: Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related STEM field.

• C++ Proficiency: Strong foundational knowledge of C/C+++ in an embedded context (you should know your way around pointers and memory management).

• Embedded Curiosity: Prior experience (via internships or high-level student projects) with bare-metal programming or an RTOS .

• Linux/Git: Comfortable working in an Ubuntu/Linux environment and using Gitfor version control.

• Problem Solver: A "builder" mindset—you enjoy debugging at the register level as much as you do writing high-level logic.

• Communication: Ability to explain a technical bug and your proposed fix clearly to the team.

• Physical: Ability to lift/carry up to 40 lbs (for moving test rigs and hardware benches).

• F' Familiarity: Previous exposure to the F-prime framework or similar component-based architectures.

• Networking: Understanding of the OSI model and basic networking protocols.

• Testing Frameworks: Experience with GTest, PyTest, or CI/CD pipelines.

• Hardware Tools: Familiarity with oscilloscopes, logic analyzers, or multimeters for debugging.

• AI/ML: An interest in or exposure to deploying Machine Learning models on edge devices.

• Salary range: $100,000 - $120,000 / per year.

• This role is on-site in Hawthorne, CA

• Unlimited PTO

• Catering provided on-site everyday.