Job Description & Details
This is a hands-on R&D software engineering role building intelligent, field-deployable medical technologies for national security applications. You will be bridging the gap between cutting-edge AI research and rugged, real-world operational hardware.
What You'll Actually Be Doing
You will spend your days bridging the gap between custom Android smartphone apps, Windows desktop environments, and low-level hardware like microcontrollers. Expect to architect new systems from scratch, integrate physical sensors, and deploy on-device machine learning models that can function in resource-constrained, high-stress environments. Since this is an R&D setting, requirements are often open-ended, meaning you will need to rapidly prototype, test, and iterate on solutions with a multidisciplinary team of scientists and engineers.
The Core Tech Stack
You need a broad, full-stack foundation with heavy emphasis on Android development and C++ Windows applications. The team relies on AWS for cloud capabilities, JSON and XML for data interchange, and deep on-device ML/LLM deployment knowledge to push artificial intelligence straight to the edge. Knowing how to interface software with microcontrollers like Arduino or Raspberry Pi is non-negotiable because your code won't just live in a browser—it has to talk to physical hardware.
Interview Expectations
The hiring managers will likely ask you to explain how you would optimize an on-device machine learning model to run efficiently on an Android device with limited memory and battery. They want to see how you balance accuracy constraints with performance bottlenecks in resource-constrained environments. Additionally, expect a deep dive into your C++ and Android background, where they'll test your ability to debug complex threading issues and hardware communication protocols under pressure.
Application Advice
To make it past the ATS, your resume needs to explicitly highlight your experience taking machine learning models off the cloud and running them natively on mobile or edge devices. Ensure keywords like Android development, C++ Windows applications, microcontroller integration, and AWS are front and center. Frame your past projects around end-to-end prototyping and hardware-software integration rather than just standard web or enterprise app delivery.