At Sphaira, we’re redefining indoor mobility with robotics and AI. As part of our mission to build autonomous platforms for hospitals and other complex environments, we’re developing advanced audio systems to enable spatial awareness and intelligent control.
We’re looking for a curious, hands-on Audio DSP intern or working student to support the design and testing of our next-generation embedded audio systems.
You’ll work directly with real hardware, contribute to DSP algorithms, and gain experience at the intersection of robotics and acoustics — all in the final stages of a product that will soon improve the lives of vulnerable patients and their families.
Tasks
- Research, prototype, and test audio signal processing algorithms
- Implement DSP algorithms on embedded platforms (e.g. SigmaDSP)
- Develop and evaluate spatial audio techniques for dynamic multi-channel routing
- Set up and wire audio hardware, including microphones, amplifiers, and speakers
- Evaluate speaker and microphone performance in mobile environments
- Document your development process and results for internal use
Requirements
- Enrolled in a university program in Audio Engineering, Signal Processing, Computer Science, Electrical Engineering, or related field
- Solid understanding of DSP fundamentals (e.g. Fourier analysis, filtering, audio signal flow)
- First experience with prototyping and wiring audio components
- Comfortable working on physical systems in a lab or test setup
Bonus Skills
- Familiarity with Analog Devices SigmaStudio or similar DSP platforms
- Experience with embedded audio systems and real-time processing
- Practical experience designing or testing speaker systems
Benefits
- A hands-on role with real embedded audio hardware
- Insights into audio R&D and product development in a robotics startup
- Flexible hours and a supportive, ambitious team environment
- The chance to contribute to a meaningful, real-world healthcare application
Ready to shape the future of sound in robotics?
Apply now and join us in building the acoustic intelligence of intramobility.