AI Programming & Development — applying machine learning and AI-assisted engineering practices to manufacturing data, quality analytics, and the software delivery lifecycle
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• Analyze software requirements to assess feasibility, considering quality, performance, time, and budget constraints.
• Collaborate with front-end architects, hardware engineers, test engineers, and other stakeholders to ensure optimal feature implementation and integration.
• Write clean, well-documented, and testable C/C++ code for embedded systems, adhering to coding standards and best practices.
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Utilizes appropriate tools and equipment to perform necessary design work including design creation, design analysis, and design verification.
Produces comprehensive project documentation based on the needs of the project and in accordance with the quality and change management procedures and guidelines.
Bachelor’s Degree required with 1 or more years of related experience preferred.
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API & System Integration – Integrate APIs, third-party services and internal microservices to build seamless and scalable solutions.
Code Quality & Performance Optimization – Participate in code reviews, maintain clean coding standards, improve the existing codebase, and optimize database queries and overall system performance.
Mentor & Collaborate – Provide guidance to junior developers, actively participate in code reviews and technical discussions, and work closely with senior developers, product managers and AI teams to deliver high-quality solutions.
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Support the design and implementation of data analytics and reporting solutions to generate operational insights and drive data-informed decision-making.
Contribute to process digitalisation and continuous improvement initiatives aimed at enhancing operational efficiency and user experience.
Prepare and maintain technical documentation, user guides, reports, presentations, and project summaries to support knowledge sharing and project governance.
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Support the design and implementation of data analytics and reporting solutions to generate operational insights and drive data-informed decision-making.
Contribute to process digitalisation and continuous improvement initiatives aimed at enhancing operational efficiency and user experience.
Prepare and maintain technical documentation, user guides, reports, presentations, and project summaries to support knowledge sharing and project governance.
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