Process Engineer - AI and Machine Learning

controlrooms.ai • United Arab Emirates
Remote
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AI Summary

Join ControlRooms.ai as a Process Engineer with hands-on plant operations experience to support industrial customers worldwide. Apply AI and machine learning software to improve real-world industrial performance. Ideal for process engineers, operations engineers, or production engineers with experience in refining, ammonia production, LNG, and polyethylene or other petrochemical plants.

Key Highlights
Support deployment, validation, and tuning of AI/ML-driven alerts and diagnostic insights
Analyze plant operating data to identify abnormal conditions, alarm patterns, and root causes
Collaborate closely with customer-facing teams to ensure models reflect real plant behavior
Technical Skills Required
AI Machine Learning Industrial Plant Operations Refining Ammonia Production LNG Polyethylene Petrochemical Plants
Benefits & Perks
Remote work
Opportunity to apply real plant experience to high-impact ML products
Influence how the platform evolves
Help bring advanced AI capabilities into industrial environments

Job Description


ControlRooms.ai is hiring a Process Engineer with hands-on plant operations experience to join our Process Engineering team, supporting industrial customers around the world. This is a fully remote role, and ControlRooms.ai operates as a remote-first company.


This role is ideal for a process engineer, operations engineer, or production engineer who has worked in operating plants and is interested in applying AI and machine learning software to improve real-world industrial performance.


Experience in refining is preferred. We also value experience in other large-scale industrial operations, including ammonia production, LNG, and polyethylene or other petrochemical plants.


This is a customer-facing role for someone who enjoys troubleshooting, understands how plants actually operate, and has an affinity for modern software, data, and emerging technologies.


Responsibilities

  • Support deployment, validation, and tuning of AI/ML-driven alerts and diagnostic insights for operating plants
  • Analyze plant operating data to identify abnormal conditions, alarm patterns, and root causes
  • Collaborate closely with customer-facing teams to ensure models reflect real plant behavior
  • Improve plant troubleshooting and reliability by reducing mean time to detection (MTTD) and mean time to resolution (MTTR)
  • Act as a technical partner to customers, translating operational knowledge into practical, data-driven insights
  • Participate in occasional domestic and international travel to customer sites as needed (generally less than 25% travel)


Qualifications

  • 2+ years of experience in process engineering, operations engineering, or production engineering (5+ years preferred)
  • Hands-on experience in industrial plant operations, including refineries, ammonia plants, LNG facilities, polyethylene, or other continuous-process operations
  • Comfort working directly with customers and communicating technical concepts clearly
  • Demonstrated curiosity or interest in industrial software, analytics, AI, or machine learning
  • Fluent in English, with the ability to communicate clearly in both written and spoken contexts
  • B.S. in Chemical Engineering preferred, but not required depending on depth and relevance of experience


Why Join ControlRooms.ai?

ControlRooms.ai builds cutting-edge AI and machine learning software for industrial operations. Our platform is deployed at complex plants globally and is helping customers unlock millions of dollars in value through improved reliability, faster troubleshooting, and better operational decision-making.


You’ll join a fast-scaling, highly technical, remote-first team working at the intersection of process engineering, data, and modern software. This role offers the opportunity to apply real plant experience to high-impact ML products, influence how the platform evolves, and help bring advanced AI capabilities into industrial environments that are rapidly adopting them.


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