About the Role
L3 Business Group is growing its R&D software team and is looking for a hands-on Embedded Software Engineer to take ownership of the firmware and embedded intelligence on AI-powered edge energy controller.
You will be the primary engineer responsible for translating AI and signal-processing algorithm specifications from our international research partners into production-grade embedded software for commercial deployment.
We work across both high-compute edge platforms and resource-constrained microcontroller environments — and are looking for an engineer who is technically versatile across this range. You will work directly with our System Architect and international R&D research partners, in a small and technically serious team where your contributions have direct impact from day one.
Key Responsibilities
- Own the firmware and embedded intelligence for our edge AI energy controller — across both ARM Cortex-A (high-compute edge inference) and ARM Cortex-M (resource-constrained, cloud-assisted) platforms
- Implement and optimise AI and signal-processing algorithms from research specifications — translating from Python/MATLAB prototype into production C/C++ embedded code
- Develop lightweight signal filtering, pre-processing, and event detection pipelines for constrained microcontroller environments (Cortex-M / RTOS)
- Develop and maintain drivers, hardware abstraction layers, peripheral management, and ADC sensor integration (voltage and current sampling)
- Design and implement efficient data pipelines between the edge controller and cloud platform — including signal compression, transmission optimisation, and communication protocol management
- Work closely with the Data & ML Platform Engineer on controller-to-cloud interface design
- Implement secure OTA firmware update mechanisms
- Maintain clear technical records of algorithm implementation decisions — separating research-partner specifications from original software implementation (important for IP documentation)
- Analyse field performance data and feedback from deployment teams to identify firmware improvement opportunities and drive iterative software refinement
- Prepare technical documentation, system notes, and test logs
Requirements
- Minimum 2–3 years of hands-on embedded software experience on real deployed hardware
- Fresh graduate with strong demonstrable embedded hardware project experience and exceptional C/C++ coding ability may be considered
- Proficiency in C/C++ for embedded systems — production code standard
- Experience with ARM processors — Cortex-A (embedded Linux) and/or Cortex-M (RTOS, bare-metal)
- Familiarity with embedded Linux, Yocto, or Buildroot for Cortex-A platforms
- Experience with RTOS environments (FreeRTOS, Zephyr, or similar) for Cortex-M platforms is a strong plus
- Solid understanding of SPI/I2C/UART, GPIO, ADC/DAC interfaces and peripheral integration
- Hands-on debugging experience with real hardware (oscilloscope, logic analyser, JTAG)
- Ability to read and implement from algorithm specifications — must understand signal processing concepts well enough to implement them faithfully and efficiently in embedded code
- Experience designing efficient data transmission pipelines between edge devices and cloud backends
- Strong documentation discipline — this role produces formal technical records, not just code
- Able to work independently and collaboratively in an R&D environment with international research partners
- Singapore Citizen or Permanent Resident preferred
Good to have:
- Experience with signal processing, DSP, embedded ML, or model inference on edge devices
- Familiarity with low-power microcontroller design and power optimisation techniques
- Familiarity with OTA update systems, MQTT, REST, or IPC frameworks
- Exposure to energy metering, power quality monitoring, or IoT sensor systems
Career Growth
You will work directly with our System Architect and international R&D partners throughout the initial development phase. As you deepen your understanding of both the embedded platform and the algorithm domain, the natural growth path is toward Lead Embedded Software Engineer — taking architectural ownership of the firmware platform, mentoring engineers joining the team, and becoming the primary technical authority on the edge intelligence layer of our system.
In this company, the software you build is the asset. You will grow with it.