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We are seeking a Senior AI/ML Engineer with strong technical depth and leadership experience to deliver advanced AI solutions in complex industrial environments. You will work with cross‑functional teams to build scalable models, optimize operations, and drive data‑driven decision‑making across large‑scale process facilities.
Job Responsibility:
Develop dynamic process simulation models and plant scenario analyses
Perform exploratory data analysis, data preprocessing, and trend identification
Build classical ML models, soft sensors, and reinforcement learning solutions for autonomous process control
Design AI systems for troubleshooting plant upsets and supporting asset performance management
Apply Generative AI, RAG, vector embeddings, and multi‑agent systems for industrial decision‑making
Deploy scalable AI models across industrial platforms and integrate with PLC, DCS, SCADA, historians, MES/MOM, EAM, SCM, and ERP systems
Ensure adherence to ethical AI principles, including fairness, transparency, and bias mitigation
Lead and mentor ML engineers and process engineers
Guide development of accurate dynamic simulation models
Promote best practices in data analysis, feature engineering, and model development
Work closely with domain experts and project managers to translate operational challenges into AI‑driven solutions
Communicate technical outcomes clearly to both technical and non‑technical stakeholders
Ensure solutions meet industry regulations, safety standards, and data governance requirements
Identify and mitigate risks related to data privacy, model bias, and operational safety
Requirements:
Bachelor’s or Master’s in Chemical Engineering, AI/ML, or related field
10+ years of hands‑on AI/ML experience, including 4+ years in a senior or lead role
Proven project delivery in industrial or energy sectors (oil & gas preferred)
Strong understanding of process engineering, instrumentation, and control systems
Experience developing dynamic process simulations using PFDs and P&IDs
Expertise with large‑scale, time‑series, and sensor/IoT data
Strong background in supervised, unsupervised, deep learning, and reinforcement learning
Experience with Generative AI, RAG, vector embeddings, and multi‑agent systems
Cloud deployment experience (AWS, Azure, or GCP) and edge AI for real‑time operations
Python and Visual Basic
Numpy, Pandas, Scikit‑learn, TensorFlow, Keras
Experience integrating AI/ML into industrial control systems and dashboards
Strong analytical and problem‑solving skills
Excellent communication and collaboration abilities
Passion for applying emerging technologies to real‑world industrial challenges
Fast learner with a proactive, team‑oriented mindset