Graduate Engineer - ESP Calculations & Machine Learning

About nybl:

We are developing an Ai ecosystem that enables businesses, in any industry, to be able to deploy artificially intelligent solutions using both our platform and applications. Our technology allows anyone to build Ai solutions without writing a line of code or needing a degree in Data Science. Our ecosystem is world changing from healthcare to agriculture, education to industry, the applications of our technology are truly limitless.

We're on the hunt for an enthusiastic Junior Engineer to help with engineering calculations and machine learning algorithms for Electrical Submersible Pumps (ESPs). This position is perfect for someone who has a solid technical foundation in petroleum, electrical, or mechanical engineering, is keen on production optimization, and loves using data science and programming to tackle real-world issues in the energy field.

• Gather, organize, and examine ESP field data (production, electrical, and fluid characteristics).
• Help in creating and verifying ESP performance calculations (head, power, efficiency, pumpability ranges).
• Apply correlations for fluid characteristics and IPR/VLP models.
• Assist in designing and testing machine learning models for optimizing ESP and predicting failures.
• Create and update Python/Excel/MATLAB scripts for engineering and ML processes.
• Record algorithms, generate reports, and present results for engineering and management teams.
• Work with senior engineers to incorporate solutions into production monitoring systems.

• Bachelor’s degree in Petroleum Engineering.
• Fundamental understanding of ESP operation and production systems (academic experience or internships are acceptable).
• Proficiency in Python (preferred), MATLAB, or VBA for engineering tasks.
• Knowledge of data analysis, regression, and basic machine learning methods.
• Analytical approach with a focus on detail and a willingness to learn.