Carbon Health is hiring an Embedded Software Engineer to push the boundaries of Edge AI. You will develop high-performance, low-latency AI models for deployment on resource-constrained devices, ensuring real-time inference in power-limited environments.
What You'll Do
- Design, train, and optimize machine learning models for deployment on microcontrollers, FPGAs, TPUs, and custom ASICs
- Implement low-power deep learning solutions for edge devices
- Optimize models using quantization, pruning, knowledge distillation, and hardware-aware training
- Deploy and benchmark ML models on TensorFlow Lite, ONNX, PyTorch Mobile, and Edge TPU
- Develop firmware/software to integrate AI models with real-time operating systems (RTOS), IoT networks, and embedded Linux
- Collaborate with hardware engineers to improve AI performance on custom architectures
What We're Looking For
- Experience in embedded software development for AI & TinyML applications
- Proficiency in C, C++, and Python for real-time, low-power systems
- Knowledge of microcontroller architectures and RTOS (Zephyr, FreeRTOS, etc.)
- Ability to work cross-functionally in a fast-moving, collaborative environment
- Passion for pushing the limits of Edge AI & embedded ML innovation
Technical Stack
- C, C++, Python
- TensorFlow Lite, ONNX, PyTorch Mobile, Edge TPU
- RTOS, Zephyr, FreeRTOS, Embedded Linux
Team & Environment
You'll join a small, focused team of 1-10 employees.
Benefits & Compensation
- Remote-first team with a flexible work culture
- Competitive salary & potential for equity/token incentives
Work Mode
This is a global remote role.
Carbon Health is an equal opportunity employer.
