Automation AI Engineer Intern

You'll make a difference by:

• Developing AI-driven optimisation agents: Design, train, and deploy AI agent models and machine learning pipelines to automatically tune, monitor, and optimise process performance across F&B manufacturing processes, including cane crushing, evaporation, crystallisation, and boiling stages.
• Bridging operational technology and artificial intelligence: Integrate real-time industrial data from DCS, SCADA, and historian systems into predictive and prescriptive AI models.
• Applying industrial control systems expertise: Utilise industrial software, such as Siemens DCS systems and AI tools, to interface automated control loops with AI-based advisory or closed-loop tuning systems.
• Executing advanced process control and tuning: Analyse process variables including temperature, pressure, flow, and levels, and implement data-driven tuning strategies to improve energy efficiency, throughput, and yield.
• Building AI and automation solutions: Combine automation engineering principles with AI technologies to develop intelligent optimisation and decision-support capabilities for manufacturing operations.
• Developing technical and AI documentation: Maintain clear documentation of AI model architectures, data pipelines, control logic, and system performance reports.

Your defining qualities:

• Pursuing or holding a relevant degree qualification: Currently enrolled in or recently graduated from a Bachelor's or Master's Degree in Automation Engineering, Mechatronics, Computer Science, Artificial Intelligence, or a related field.
• Possessing dual-domain expertise: Demonstrate a strong foundational understanding of both industrial automation, including DCS programming, PID control, and sensors, and AI/data science, including Python, machine learning, time-series analysis, or LLM and agentic workflows.
• Understanding industrial processes: Show a keen interest in, or prior exposure to, process industries and the underlying physics and chemistry of manufacturing operations.
• Applying analytical and algorithmic problem-solving skills: Translate complex factory bottlenecks into data-driven challenges and apply optimisation algorithms or AI agents to identify effective solutions.
• Leveraging relevant software and tools: Possess hands-on experience with Python (PyTorch, Scikit-learn, LangChain, LlamaIndex), database systems (InfluxDB, SQL), and industrial communication protocols (OPC UA, Modbus).
• Collaborating and learning effectively: Demonstrate strong interpersonal skills to work with plant engineers and data scientists while maintaining a proactive approach to learning industrial domain knowledge.

In return, we offer you:

• Values-Driven Culture: An inclusive workplace that prioritizes diversity and belonging.
• Continuous Learning & Development: Opportunities to grow your skills and advance your career.

Recruitment Process:

• CV Screening
• If shortlisted, a session with our TA Consultant to understand your motivation & your past experiences
• 1-2 Business Interviews
• Offer Stage