Edge AI Intern — C++ / Linux / Python

Edge AI Intern — C++ / Linux / Python
We are hiring an Edge AI Intern who enjoys working close to the hardware and wants to understand how AI systems actually run outside notebooks and demos.
This internship is about building end-to-end AI systems that ship — not just PoCs.
You will work on systems where execution time, memory usage, parallel processing, hardware limitations, reliability, and the end-user experience matter as much as model accuracy.
What we are looking for
You should have a good foundation in:
C++
Linux
Python
Compilation and build fundamentals
Basic computer hardware and system architecture
Memory, CPU/GPU usage and execution-time awareness
Good communication skills
You do not need to be an expert yet. But you should be genuinely interested in understanding what happens underneath the code.
You will enjoy this role if you like
Playing with hardware, cameras, sensors, GPUs or embedded devices.
Compiling things, debugging things and occasionally figuring out why something works perfectly on your laptop but not on the target device.
Thinking about questions like:
Can this run faster?
Can we reduce memory usage?
Can these tasks execute in parallel?
What happens when hundreds or thousands of users/devices use this system?
What pain will the end user experience?
We build AI systems intended for real-world deployment and scale, not experiments that stop after model inference works.
Preferred Educational Background
Students or recent graduates from:
Electronics & Communication Engineering
Instrumentation & Control Engineering
Computer Science / Computer Engineering
Related engineering disciplines
What matters most
Ownership mindset and clear communication.
We are looking for someone who does not stop at:
“My code is working.”
Instead, you should naturally think:
“Is the entire system working properly for the user?”
You should be able to explain technical problems clearly, communicate blockers early, discuss trade-offs with the team, and take responsibility for moving the work forward.
You should be curious, willing to debug across software and hardware, comfortable learning independently, and interested in taking a problem from AI model → software → hardware → production system.
If you want to build AI that actually runs in the real world, we would like to hear from you.

Work arrangement
No