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STMicroelectronics

Manufacturing Data Science - IPP - Expert System

STMicroelectronics
Integrated Device ManufacturingSingapore, SingaporeFull-time1 months ago
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About the role

AI summarised

This is a mid-level data science role at STMicroelectronics, a global semiconductor company. The position focuses on designing and building agentic AI-driven expert systems for predictive and autonomous decision-making in manufacturing, involving multiagent AI, simulation, digital twins, and integration of predictive models.

IDMFull-timeData Science

Key Responsibilities

  • Design and build agentic AI–driven expert systems that enable predictive and autonomous decision making in manufacturing.
  • Develop agent based and multiagent AI systems that can plan, decide, and act on behalf of operators, equipment, or production lines.
  • Design reasoning and decision policies that leverage rules, optimization, and learning to handle complex, real time manufacturing scenarios (e.g. dispatching, scheduling, routing, quality control).
  • Use simulation and digital twins to model production flows, equipment behavior, and system constraints, and to safely test and refine agent strategies before deployment.
  • Integrate predictive models (e.g. for demand, machine health, cycle time, yield) into expert systems to support proactive and prescriptive decisions.
  • Collaborate closely with process owners, planners, and equipment engineers to translate operational knowledge into rules, heuristics, and agent objectives.
  • Evaluate agentic AI solutions using KPIs such as throughput, WIP, cycle time, OEE, and cost, and iteratively improve performance.
  • Document architecture, algorithms, experiments, and support presentations, publications, and IP creation related to expert and agentic AI systems.

Requirements

  • Bachelor or master's in computer science, AI, Data Science, Operations Research, Industrial/Electrical Engineering, or similar.
  • Strong foundation in AI and machine learning, with exposure to at least one of: Reinforcement learning / multiagent RL, Planning and decision making under uncertainty, Rule based or knowledge-based systems.
  • Experience with Python and AI/ML ecosystems (e.g. PyTorch, TensorFlow, scikitlearn, RL libraries).
  • Familiarity with simulation and modeling of manufacturing or logistics systems (e.g. discrete event simulation, agent-based simulation, digital twins).
  • Understanding of operations research / optimization (e.g. scheduling, routing, resource allocation) is a strong plus.
  • Comfortable working with real operational and equipment data, including cleaning, feature engineering, and validation.
  • Strong analytical and conceptual skills, able to formalize complex shopfloor logic into rules, constraints, and agent objectives.
  • Collaborative, curious, and proactive, able to work with cross functional teams and incorporate domain expert feedback into AI systems.
  • English business proficiency, both written and spoken, for documentation, stakeholder discussions, and technical presentations.