*For Singapore Applicants Only: PC Partner Technology Pte Limited will be prioritising applicants who have a current right to work in Singapore, and do not require PC Partner Technology Pte Limited's sponsorship of a visa.

Overview

Founded in Hong Kong in 1997, PC Partner has grown from a small contract manufacturer with fewer than 300 employees to a global leader in computer electronics. We design and sell our own branded products, including video graphics cards, Mini-PCs, motherboards, embedded systems, and gaming hardware, while also providing one-stop electronic manufacturing services to reputable brands worldwide. Leveraging our advanced R&D capabilities and state-of-the-art production facilities, we continually introduce innovative products to the market, staying ahead of industry trends to ensure competitiveness and meet the evolving needs of our customers.

Position Summary

We are seeking an AI Engineer to drive the design and deployment of advanced AI solutions. The role involves selecting and implementing optimal AI models, as well as building data engineering pipelines to support machine learning model training, evaluation and deployment. You will collaborate closely with cross-functional teams to innovate, execute and deliver AI technologies, ensuring project success through strong technical expertise, effective teamwork and clear communication.

Key Responsibilities

• Collaborate with cross-functional teams to define technical specifications for AI-driven software solutions.

• Build and maintain robust, scalable data pipelines to support machine learning and AI model training.

• Design and manage data architectures that enable efficient and reliable AI workflows.

• Prepare, clean, and integrate large datasets; design and implement vector databases to support training and inference of machine learning models.

• Design and develop AI models and APIs, integrating them seamlessly into both application software and embedded hardware systems.

• Review codes developed by team members, driving continuous improvement of AI models through algorithm refinement, code optimisation, and stakeholder feedback.

• Develop comprehensive test cases; conduct rigorous testing, debugging and bug fixing to ensure high quality, performance and system reliability.

• Train, evaluate and fine-tune machine learning models to achieve optimal efficiency and low latency.

• Implement MLOps best practices to manage the end-to-end software and machine learning lifecycle, including version control, CI/CD pipelines, and documentation.

• Collaborate with project leaders to plan, execute, monitor, and deliver multiple projects using Agile methodologies.

• Work closely with project teams to deploy machine learning models into production environments and support post-deployment operations.

• Analyse data to extract meaningful insights and present results to stakeholders to support product and business decisions.

• Conduct research and collaborate with external stakeholders to stay up to date with the latest AI technologies and industry standards, continuously enhancing development and evaluation processes.

Requirements

• Min. Degree in Computer Science, Computer Engineering, Data Science, Artificial Intelligence or related fields.

• Min. 2 years of relevant experience in a similar role, with hands-on experience in designing, developing and deploying machine learning in real-world applications.

• Proficient in machine learning frameworks and libraries such as TensorFlow and PyTorch, particularly for computer vision tasks including object detection, classification and tracking.

• Familiarity with relational database management systems (RDBMS) such as PostgreSQL and Microsoft SQL Server, as well as experience with vector databases.

• Experience in application software development across multiple platforms including Windows, Linux, mobile operating systems (iOS, Android) and embedded systems.

• Strong programming skills in Python, Java and C++, with experience in GPU-accelerated computing using CUDA and TensorRT.

• Knowledge of edge computing platforms and hardware accelerators such as NVIDIA Jetson, Google Coral, and ARM Cortex.

• Excellent written and spoken English communication skills, fluency in Chinese is a plus for effective interaction with Chinese-speaking stakeholders.

• Candidates must meet legal requirements to work in Singapore without sponsorship.

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