Embedded AI Systems Engineer

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

About the Role

Our client, a leader in the Internet of Things (IoT) and intelligent hardware solutions, is seeking an Embedded AI Systems Engineer to join their innovative R&D team in Nelspruit, Mpumalanga . This role focuses on integrating artificial intelligence and machine learning capabilities into embedded systems, enabling devices to perform intelligent tasks locally. You will be involved in the entire product lifecycle, from conceptualization and design to implementation and testing of AI algorithms on resource-constrained hardware. The ideal candidate has a strong background in embedded systems development, a solid understanding of ML concepts, and experience optimizing models for edge devices. This is a challenging and rewarding opportunity to work at the intersection of AI and embedded systems in Nelspruit, Mpumalanga .

Key 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.

Requirements

• 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 (e.g., I2C, SPI, UART).
• Ability to analyze performance metrics and identify optimization opportunities.
• Strong problem-solving and debugging skills in a hardware/software environment.
• Good communication and teamwork skills for a hybrid setting in Nelspruit, Mpumalanga .

Benefits

• Competitive salary and performance-based bonuses.
• Hybrid work model offering flexibility.
• Comprehensive health and wellness benefits.
• Opportunities for professional development and learning new technologies.
• Engaging projects involving cutting-edge embedded AI technology.
• Supportive team environment with a focus on innovation.
• Access to advanced development tools and equipment.
• Contribution to the future of intelligent embedded devices in Nelspruit, Mpumalanga .