Qualcomm Technologies Netherlands B.V. is a global tech leader that has joined forces with Edge Impulse to grow its team focused on Edge AI. The role involves enabling developers to create intelligent device solutions with embedded Machine Learning, expanding embedded edge devices, and developing algorithms for data processing.
Responsibilities:
- Expand the fleet of embedded edge devices that support machine learning
- Develop code that enables Edge Impulse Machine Learning onto embedded devices using modern software development and deployment tools
- Connect sensors (image, audio, motion) to Edge Impulse applications
- Develop algorithms for data / image processing
- Improve / develop tooling that connects an embedded system to a larger system
- Drive solutions forward with an ownership mindset working effectively both independently and as a member of a distributed team
Requirements:
- A minimum of 7 years of experience in embedded software development
- Proficient writing code in C/C++ and familiarity with Python, Typescript, shell, and other scripting languages
- Proven experience delivering technical projects on embedded processors using an understanding of processor architecture and peripheral control
- Embedded development tools (GCC, Make, CMake)
- Debugging tools
- Operating systems (like Embedded Linux and Android) targeted for embedded devices
- Experience with developing computer vision applications
- Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Systems Engineering or related work experience
- OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 3+ years of Systems Engineering or related work experience
- OR PhD in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience
- Experience as bringing creative solutions to challenging problems and working hands-on to build IoT / embedded ML solutions
- Exposure to the following technologies would be useful: Embedded Machine Learning, GStreamer, OpenCV, Buildroot / Yocto distributions, Linux Kernel and/or Linux driver development