Back
Mid-level AI role in metro with broad ML/LLM and MLOps requirements increases candidate competition.
Core ML skills are transferable, but DCS and power-plant domain experience increase industry specificity.
Explicit 2–5 years requirement plus mandatory ML, MLOps, and industrial domain expertise raise shortlisting rigidity.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop AI/ML solutions to automate control logic, graphics, reporting, and workflow to improve engineering productivity and plant operations.
Create predictive tools, dashboards, and intelligent support systems including generative AI and natural language processing for data-driven decision-making and safety enhancement.
Collaborate with engineers and operators to design secure, compliant, and reliable AI tools that integrate within industrial automation workflows, focusing on predictive maintenance and anomaly detection.
Bachelor's degree or equivalent in Engineering, AI, Data Science, Electrical/Computer Engineering, or related field.
2–5 years of experience in AI/ML model development, deployment, and optimization in real-world applications.
Proficiency in Python and frameworks like TensorFlow/PyTorch; experience with MLOps.
Experience in AI applied to industrial environments, preferably in power plant operations or similar control systems.
Expertise in machine learning, deep learning, generative AI, including LLMs, with a focus on automation and decision support.
Experience in power plant operation domains such as boilers, turbines, combustion, control theory, and integration with systems like Emerson Ovation DCS.
Skilled in predictive maintenance, anomaly detection using time-series data, and committed to responsible AI practices ensuring explainability and safety in critical infrastructure.