About The Company

Join a pioneering R&D-driven tech company on a mission to bridge the frontier between machine learning and embedded systems. With a focus on real-world applications in AI, low-power devices, and edge intelligence, our team is building practical solutions that are reshaping how data is processed where it's generated—on the edge. Backed by seasoned deep-tech engineers, this company works across domains from computer vision to embedded AI, building systems that bring AI inference to ultra-low power hardware environments.

About The Role

We’re looking for a hands-on Embedded Software Engineer (AI/ML) to lead the implementation and optimization of ML models for low-power microcontrollers. If you’re excited about putting ML to work on constrained devices, love diving deep into firmware performance tuning, and are passionate about building real products, not just demos, this role is for you.

You will work closely with a team of AI scientists and hardware engineers to bring ML inference to life on microcontrollers like the ESP32-S3 and ARM Cortex-M series.

Key Responsibilities

• Develop and maintain embedded firmware (C/C++) for microcontroller platforms (ESP32, ARM Cortex-M).
• Integrate AI models using frameworks such as TensorFlow Lite for Microcontrollers (TFLM).
• Optimize AI model performance using quantization and hardware acceleration (DSP, SIMD).
• Implement and fine-tune sensor drivers (camera, mic, IMU) over I2S, SPI, DMA.
• Manage and schedule ML inference tasks in FreeRTOS while maintaining system stability.
• Profile and debug for performance: speed, memory, and power consumption.
• Collaborate with AI researchers to translate models into efficient edge-compatible implementations.
  
  

Qualifications

Must-Have

• 5+ years of experience in embedded systems and firmware development.
• Proficiency in C and C++ for real-time embedded environments.
• Solid understanding of FreeRTOS, and communication protocols (I2C, SPI, I2S).
• Familiarity with AI/ML fundamentals: neural networks, inference vs. training.
  
  

Nice-to-Have

• Hands-on experience with TFLM, Edge Impulse, or other on-device ML tools.
• Knowledge of ESP32 and esp-idf development.
• Python scripting for data and ML preprocessing.
• Experience in on-device CV or audio signal pipelines.
• Exposure to low-power embedded design for battery-powered systems.
  
  

Why Join Us?

• Tackle real engineering challenges—not SDK demos or sandbox projects.
• Work at the intersection of Embedded Systems & AI—a rapidly growing field with deep impact.
• Collaborate in a startup-like, product-first culture that values ownership and creativity.
• Be part of a tight-knit team building cutting-edge edge AI products from Vietnam to the world.
  
  

Location

📍 27D Quoc Huong, Thao Dien, Thu Duc City, HCMC

Ready to build the future of on-device AI?

Apply now and join a team that’s redefining the limits of embedded intelligence.