Hybrid Embedded AI Engineer: Edge ML & TinyML

Placements24; Mbombela (Nelspruit); Hybrid; ZAR 700,000 - 1,100,000; Full time

Benefits offered by this job

Hybrid work model

Performance bonuses

Health benefits

Professional development

Advanced development tools access

Job summary

Placements24 is seeking an Embedded AI Systems Engineer to join its R&D team in Nelspruit, Mpumalanga. You will design, develop, and optimize AI/ML algorithms for deployment on embedded hardware, focusing on resource-constrained devices and edge inference.

The role requires strong C/C++ and embedded systems experience, familiarity with ML frameworks, and a passion for TinyML. Hybrid work arrangements and ongoing professional development are offered.

Qualifications

• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• 3+ years of experience in embedded systems development, with C/C++ proficiency.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow Lite, PyTorch Mobile, scikit-learn).
• Understanding of ML model optimization techniques for embedded and edge devices.
• Familiarity with microcontroller architectures and real-time operating systems (RTOS).
• Experience with sensor integration and data acquisition.
• Knowledge of common communication protocols used in embedded systems (I2C, SPI, UART).
• Strong problem-solving and debugging skills in a hardware/software environment.
• Good communication and teamwork skills for a hybrid setting in Nelspruit, Mpumalanga.

Responsibilities

• Design, develop, and optimize AI/ML algorithms for deployment on embedded systems and microcontrollers.
• Implement efficient ML models for edge devices, considering computational and memory constraints.
• Integrate AI functionalities with existing embedded software and hardware components.
• Develop and execute testing strategies for embedded AI systems, including unit, integration, and system testing.
• Collaborate with hardware engineers to define system requirements and select appropriate components.
• Optimize model inference speed and power consumption on target hardware.
• Work with sensor data and implement pre-processing techniques for embedded AI applications.
• Stay current with advancements in embedded AI, TinyML, and edge computing.
• Troubleshoot and debug complex issues in embedded AI systems.

Skills

C/C++

Embedded systems

Sensor integration

RTOS

Debugging

Teamwork

Education

Bachelor's or Master's in Electrical/Computer Engineering/CS

Tools

TensorFlow Lite

PyTorch Mobile

scikit-learn

Job description

Placements24 is seeking an Embedded AI Systems Engineer to join its R&D team in Nelspruit, Mpumalanga. You will design, develop, and optimize AI/ML algorithms for deployment on embedded hardware, focusing on resource-constrained devices and edge inference.

The role requires strong C/C++ and embedded systems experience, familiarity with ML frameworks, and a passion for TinyML. Hybrid work arrangements and ongoing professional development are offered.