AI Engineer

JOB SUMMARY  
The AI Engineer is responsible for designing, developing, and deploying AI and machine learning solutions to support data-driven decision-making across subsurface, laboratory, and production domains. 

This role focuses on building scalable AI/ML models that can translate complex engineering and operational challenges into practical, high-impact solutions. Working closely with reservoir engineers, laboratory teams, and business stakeholders, the AI Engineer will bridge advanced 
analytics with real-world energy applications. 

The successful candidate will bring strong technical expertise in machine learning, data engineering, and software development, with the ability to turn complex datasets into actionable insights and scalable tools. 

KEY RESPONSIBILITIES 
• Design, develop, and deploy machine learning models for real-world applications across energy and industrial datasets  
• Translate business and engineering problems into AI-driven solutions  
• Build and maintain scalable data pipelines and data processing workflows  
• Apply advanced analytics to subsurface, production, and laboratory data  
• Collaborate with multidisciplinary teams to integrate AI solutions into existing workflows  
• Optimize and monitor model performance, ensuring accuracy, scalability, and reliability  
• Implement best practices in model validation, testing, and deployment  
• Develop dashboards, tools, or applications to visualize and communicate insights  
• Stay updated with emerging AI/ML technologies and recommend innovative applications 

QUALIFICATIONS  
• Bachelor’s or master’s degree in computer science, Software Engineering, or a related field  
• Proven experience developing and deploying AI/ML models in real-world applications  
• Experience in data-intensive environments (energy or industrial sectors preferred) 

EXPERIENCE/KNOWLEDGE/SKILLS 

Essential 
• Strong proficiency in Python and machine learning frameworks  
• Experience developing and deploying AI/ML models in real-world environments  
• Strong background in data engineering, including data pipelines and large dataset handling  
• Experience with model evaluation, tuning, and optimization  
• Knowledge of cloud platforms or scalable infrastructure (AWS, Azure, or GCP)  
• Ability to translate complex business problems into scalable AI solutions  
• Strong problem-solving and analytical thinking skills s              

Preferred 
• Experience working with energy, oil & gas, or industrial datasets  
• Exposure to time-series forecasting, predictive maintenance, or optimization models  
• Familiarity with reservoir engineering, production data, or laboratory datasets  
• Experience with big data tools (e.g., Spark, Hadoop)  
• Knowledge of MLOps practices and model lifecycle management  
• Experience building user-facing tools, dashboards, or APIs 

ADDITIONAL SKILLS/REQUIREMENTS 
• Strong communication skills with the ability to explain technical concepts to nontechnical stakeholders  
• Ability to work collaboratively across engineering, data, and business teams  
• Adaptability in a fast-paced, innovation-driven environment  
• Proactive mindset toward continuous improvement and innovation