We are seeking an Edge AI & Embedded ML Engineer to develop high-performance low-latency AI models for deployment on resource-constrained devices. This role involves optimizing deep learning models for real-time inference on edge hardware ensuring efficiency in power-limited environments.
If you have experience with TinyML on-device AI and embedded neural networks this is the perfect opportunity to work on cutting-edge innovations.
Tasks
- 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
Requirements
- 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
Benefits
Work on the bleeding edge of blockchain & AI innovation.
Remote-first team with a flexible work culture.
Opportunity to shape the future of decentralized AI applications.
Competitive salary & potential for equity/token incentives.
Join Avo Intelligence and revolutionize AI! Work with cutting-edge TinyML tech collaborate globally and make an impact. Apply now for the Embedded Software Engineer role!
We are seeking an Edge AI & Embedded ML Engineer to develop high-performance low-latency AI models for deployment on resource-constrained devices. This role involves optimizing deep learning models for real-time inference on edge hardware ensuring efficiency in power-limited environments.If you have...
We are seeking an Edge AI & Embedded ML Engineer to develop high-performance low-latency AI models for deployment on resource-constrained devices. This role involves optimizing deep learning models for real-time inference on edge hardware ensuring efficiency in power-limited environments.
If you have experience with TinyML on-device AI and embedded neural networks this is the perfect opportunity to work on cutting-edge innovations.
Tasks
- 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
Requirements
- 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
Benefits
Work on the bleeding edge of blockchain & AI innovation.
Remote-first team with a flexible work culture.
Opportunity to shape the future of decentralized AI applications.
Competitive salary & potential for equity/token incentives.
Join Avo Intelligence and revolutionize AI! Work with cutting-edge TinyML tech collaborate globally and make an impact. Apply now for the Embedded Software Engineer role!
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