Design AI Engineer

Future Electronics; Singapore; On-site; SGD 50,000 - 80,000; Full time

Job summary

Future Electronics is seeking a self-motivated full-time engineer to develop, deploy, and validate AI solutions for signal-based and edge AI applications on embedded Linux platforms.

You will analyze sensor signals, perform feature extraction, evaluate AI models, and support deployment, monitoring, and validation on real hardware.

Fresh graduates or early-career candidates with strong math and ML tooling knowledge are encouraged to apply.

Qualifications

• Bachelor’s degree in CS/AI or related field.
• Fresh graduates or early-career candidates welcomed.
• Proficiency in Python, TensorFlow, PyTorch.
• Strong math background in linear algebra, probability.
• Ability to work independently and communicate clearly.

Responsibilities

• Develop AI features for sensor signals and edge devices.
• Analyze signals, extract features, and evaluate models.
• Support AI deployment on embedded Linux platforms.
• Validate AI results on real hardware.
• Collaborate with engineers to integrate AI into edge systems.

Education

Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Physics, Mathematics, Engineering, or related field

Tools

Python

TensorFlow

PyTorch

Embedded Linux

Job description

We are looking for a self-motivated full-time engineer to support the development, deployment, and validation of AI solutions for signal-based and edge AI applications.

This role focuses on applying artificial intelligence, mathematics, and signal processing concepts to analyze sensor signals, system data, and AI inference outputs from embedded devices. The engineer will be involved in signal analysis, feature extraction, AI model evaluation, edge AI deployment, embedded Linux application control, and system-level validation.

The selected candidate will support practical AI applications running on embedded Linux or edge AI platforms. Key activities include preparing signal data, analyzing normal and abnormal system behavior, supporting AI model deployment, monitoring AI application performance, and assisting engineers in validating AI results on real hardware.

This role is suitable for candidates who are interested in AI for industrial systems, signal processing, embedded Linux, edge AI deployment, sensor data analysis, and practical software-hardware integration.

JOB CONTENT:

AI and Signal Processing Development

• Analyze sensor signals, electrical signals, audio signals, vibration signals, image data, or other system data for AI-based applications.


• Support the development of AI features for classification, detection, monitoring, or prediction.


• Work with engineers to identify meaningful signal patterns and convert them into usable AI model inputs.


• Assist in preparing datasets for AI model development, testing, and validation.


• Work with engineers to design AI models for specific application requirements.


• Support AI model evaluation using metrics such as accuracy, false positive rate, false negative rate, precision, recall, and confusion matrix analysis.


• Support feature engineering and data visualization to better understand AI model behavior.

Embedded AI System Integration

• Support the integration of AI applications into embedded Linux platforms and AI-enabled MCUs.


• Assist in setting up embedded system startup behavior, application launch scripts, and runtime control flow.


• Support system-level debugging involving AI software, signal input, embedded hardware, and user interface tools.


• Assist in validating the complete workflow from signal input to AI processing and final system output

Requirements

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Physics, Mathematics, Engineering, or related field.


• Fresh graduates or early-career candidates with relevant project experience are welcome to apply.


• Good knowledge of machine learning, deep learning, data analytics, statistical modelling, and AI frameworks or tools such as Python, TensorFlow, and PyTorch.


• Strong foundation in mathematics, including linear algebra, probability, statistics, and numerical analysis.


• Strong analytical thinking skills, with the ability to learn quickly, understand requirements, adapt to new AI tools and application domains, communicate clearly, and work independently.


• Willingness to work across the full AI development workflow, including signal processing, AI modelling, embedded Linux, software integration, and system testing.