YOKOGAWA ENGINEERING ASIA PTE LTD
AI Engineer (Process Industry)
Visa Source Listed
📍🇸🇬 Singapore📅10h ago
S$96,000—S$1,20,000/ year
≈ ₹60L — ₹75L per year
Machine LearningLiaising with cross functional teamsDCSAWSArchitectCritical ThinkingArtificial IntelligenceApplication DevelopmentPredictive AnalyticsPLCComputer ScienceDelivering digital solutionsWorking alongside Product TeamsPythonArtificial Intelligence Application
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Job Description
Responsibilities
- Develop and implement AI models for predictive & prescriptive analytics in industrial applications.
- Process Optimization, and Autonomous Operations in asset-intensive industries such as Oil & Gas, Mining, and Utilities.
- Build and integrate machine learning, deep learning, and generative AI models (LLMs, RAG, multi-agent systems).
- Work with industrial data platforms (SCADA, DCS, PLC, Historians, MES, ERP) to ensure seamless AI integration.
- Deploy AI solutions in cloud-based environments, ensuring scalability and reliability.
- Apply industrial AI ethics and best practices to ensure compliance and responsible AI usage.
- Collaborate with cross-functional teams to translate AI research into practical, high-impact solutions.
Requirements
- Bachelor’s/master’s in computer science, AI, Machine Learning, or related field.
- At least 5 years of experience in applying AI/ML in asset-intensive industries such as oil & gas, utilities, or mining.
- Strong experience with Predictive Analytics and Prescriptive Analytics using tools like TensorFlow, PyTorch, and Keras.
- Proven experience in Generative AI – Meta LLaMA, OpenAI GPT, DeepSeek R1, Anthropic Claude, etc., and RAG & vector embeddings for optimized knowledge retrieval and decision-making, and multi-agent systems for industrial applications.
- Expertise in cloud-based AI deployments (AWS, Azure, or Google Cloud) and edge AI for real-time decision-making.
- Experience with SCADA, DCS, PLCs, smart sensors, IoT platforms, and Historians.
- Strong analytical, problem-solving, and communication skills, with a proven ability to work across teams.
- Experience in Reliability Analytics and Condition-Based Maintenance (CBM)
- Familiarity with multi-agent systems for collaborative decision-making and goal-seeking AI agents
- Familiarity with KPI monitoring, criticality and risk assessment, and asset strategy optimization
By responding to Yokogawa’s advertisement, consent is considered given to Yokogawa to collect the required personal data for the purpose of recruitment with expectation that Yokogawa will protect personal data with security safeguards that are reasonable and appropriate to the sensitivity of the personal data, to protect it from unauthorized access, use or disclosure and complies with applicable regulatory requirements with respect to the retention of personal data.
We regret to inform that only shortlisted candidates will be notified.