AI Engineer

About kuubiik

kuubiik is an international consulting firm headquartered in Singapore, delivering outsourcing and project-based solutions globally across more than 150 countries. Its diverse workforce spans Asia, Europe, and the Americas, with a trusted client portfolio including leading companies such as Google, TikTok, HP, and TELUS. kuubiik emphasizes adaptable outsourcing services, available on an hourly or full-time basis, focusing on client-specific needs through collaborative innovation and competitively priced, tailored solutions.

Role Details

This is a full-time, permanent position located onsite in Singapore. The official working hours are Monday through Friday from 9:00 AM to 5:00 PM Singapore Time.

Primary Responsibilities

• Develop, design, and enhance machine learning and deep learning predictive models specifically for anomaly detection, fault diagnosis, and failure forecasting.
• Conduct thorough analysis of complex, high-dimensional, and noisy IoT sensor data streams, including vibration, acoustic, thermal, and electrical signals.
• Survey and benchmark the latest academic research to incorporate pioneering condition monitoring techniques into scalable, production-ready AI algorithms.
• Plan and execute meticulous experiments to validate predictive hypotheses using real-world industrial machine failure datasets.
• Deploy scalable AI models with low latency to cloud environments such as AWS, Google Cloud Platform, or Microsoft Azure utilizing robust MLOps methodologies.
• Develop real-time operational monitoring systems for evaluating model drift, latency, and overall performance in industrial environments.
• Maintain and enhance AI algorithms by continuous retraining with live feedback, testing outcomes, and edge-case scenario data.
• Collaborate closely with engineering teams to optimize data pipelines and improve feature engineering for input data quality.
• Document system designs, performance metrics, and insights clearly for both internal teams and executive stakeholders.
• Support IoT field operations by assisting in the planning, installation, and configuration of hardware and software at client locations to ensure reliable data acquisition and system stability.

Required Skills and Qualifications

• Demonstrated expertise in machine learning, especially in complex time-series data processing, signal processing, and anomaly or failure detection.
• Proficient coding skills primarily in Python; familiarity with R or Java is advantageous.
• Experience using machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience deploying AI models on cloud platforms (AWS, GCP, or Azure) using industry-standard MLOps practices.
• Strong background analyzing physical sensor data with knowledge of Fourier transforms, vibration analysis, and metrics related to pressure and temperature.
• Excellent problem-solving abilities, able to manage and analyze noisy, incomplete, and high-dimensional datasets effectively.
• Effective communication skills to translate complex technical information to operational and business stakeholders.
• A proactive, resourceful approach suited to fast-paced, startup-like environments.
• A minimum of two years working experience in industrial, manufacturing, or heavy machinery contexts.
• Advanced understanding of data-driven as well as physics-based or model-based condition monitoring techniques.
• Experience building autonomous AI systems, root-cause analysis tools, or prescriptive maintenance solutions is preferred.