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Artificial Intelligence Engineer

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Onsite

Artificial Intelligence Engineer

Talent Link by e2i

Artificial Intelligence Engineer

Skills

Deep LearningTesting & QAData AnalysisMachine LearningAICompliance

1 month ago

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Important information


Contract type:

Permanent

Location:

Singapore

Work mode:

Onsite

Published on:

22 September 2026

What they need


Talent Link by e2i is a programme to match candidates to job opportunities offered by e2i’s Industry Partners. Applicable for Singaporeans and Singapore Permanent Residents only.

This job opportunity is from our Industry Partner in the Startup space.

Job Descriptions

  1. Predictive Maintenance AI Model Development:

○ Design and implement machine learning and deep learning models for our

Predictive Maintenance applications.

○ Optimize models for performance, scalability, and accuracy.

  1. Data Processing and Analysis:

○ Analyze, understand, and pre-process sensor data streams to identify patterns

that predict equipment and industrial asset failures beforehand.

○ Perform exploratory data analysis to identify patterns and insights.

  1. Deployment and Maintenance:

○ Deploy AI models to production environments using best practices.

○ Monitor, maintain, and update deployed models to ensure ongoing relevance and

performance.

○ Build scalable, real-time models for low-latency predictions.

  1. Collaboration and Problem Solving:

○ Collaborate with engineers to improve data pipelines and enhance model

accuracy.

○ Identify AI opportunities within existing workflows and propose innovative

solutions.

  1. Research and Innovation:

○ Stay updated with the latest advancements in AI technologies and

methodologies.

○ Research and stay up to date with academic literature and state-of-the-art

condition monitoring techniques, translating these ideas and innovations into

workable and deployable solutions.

○ Work with the engineering team to create experiments and failure datasets; you

will use real data from machines to validate your hypotheses, develop new

models, and improve current models.

  1. Performance Monitoring:

○ Develop tools and frameworks to monitor model behavior in real-time and enable

data-driven maintenance decisions.

○ Troubleshoot issues and ensure model reliability under varying conditions.

○ Continuously improve and validate models based on real-world performance, test

results, and feedback.

  1. Documentation and Reporting:

○ Document AI models, processes, and systems for internal use.

○ Create reports on AI performance metrics and insights for stakeholders.

  1. IOT Field Engineering support:

○ Plan and execute IoT hardware deployments tailored to client site requirements.

○ Perform on-site installation and configuration of our software and hardware

solutions at locations.

○ Coordinate with internal teams to ensure smooth installation, integration, and

commissioning of devices.

○ Maintain the stability and reliability of deployed IoT systems to ensure

uninterrupted data flow and operation.

○ Provide on-site and hands-on technical support to resolve client hardware-related

issues quickly.

○ Ensure all deployments adhere to safety, quality, and industry standards.

○ Work with QA to validate device performance and system reliability.

○ Ensure compliance with safety regulations and company installation standards.

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