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Linear Programming Engineer

  • Full Time
  • Toronto

Aramco


Aramco energizes the world economy.

Aramco occupies a special position in the global energy industry. We are one of the world’s largest producers of hydrocarbons and chemicals, with among the lowest upstream carbon intensities of any major producer.

With significant investments in technology and infrastructure, we aim to maximize the value of the energy we produce for the world, along with a commitment to enhancing Aramco’s societal value.


Headquartered in the Kingdom of Saudi Arabia, with offices worldwide, we combine market discipline with a long-term vision, driven by nine decades of responsible stewardship of the Kingdom’s vast hydrocarbon resources. This responsibility has enabled us to deliver significant societal and economic benefits to the Kingdom and to many communities, economies, and countries relying on our vital and reliable energy supply.

We are one of the most profitable companies globally and rank among the top five in market capitalization.

Overview

We are seeking a Linear Programming Engineer to join the Central Planning & Modeling Division.

The division is responsible for optimizing crude allocation and the operations of our global manufacturing facilities to maximize revenue, increase profitability, and explore international market opportunities. It also manages the LP gatekeeper functions for wholly owned refineries and the global MPIMS model, maintaining an integrated planning model for optimizing crude allocation and exploring new markets and integration options.

Your primary role involves consulting on complex engineering and LP problems, reviewing existing and new simulations, and updating shift vectors for sub-models within the PIMS structure. You will ensure simulation accuracy for LP backcasting, recommend improvements, and have the opportunity to develop a grassroots refinery simulation. Mentoring junior engineers and providing technical services will also be part of your responsibilities.



Key Responsibilities

  • Run rigorous simulations to identify deviations from actual conditions.
  • Operate the refinery model after short-range operating model (SROP) optimization to identify operational opportunities.
  • Define data and processes needed to maintain and update simulations.
  • Develop non-linear equations to reflect operational variables in the PIMS Advanced Optimization model.
  • Maintain the accuracy of the hybrid LP model.
  • Collaborate with process engineers to ensure accurate simulation outputs and resolve bottlenecks.
  • Perform back-casting and issue monthly reports on simulation gaps and mitigations.
  • Support stakeholders in creating models for new downstream projects.
  • Assist ASSAY experts in calibrating the True Boiling Point (TBP) and cut points to reflect actual column efficiencies.

Minimum Requirements

The ideal candidate holds a Bachelor’s degree in Chemical Engineering or a related field; an MBA or advanced degree is preferred.

  • At least 9 years of experience in consulting or refinery industries, with deep knowledge of rigorous simulation for refinery units.
  • Expertise in developing rigorous simulations to derive shift vectors and process objectives, with at least 7 years using Aspen HYSYS or PETROSIM.
  • Experience in developing simulations for hydrocracking, FCC, DHT, reforming units, and complete refinery models.
  • Strong understanding of engineering practices, economic principles, and calculations.
  • Experience in international business and cross-cultural practices.
  • Experience integrating rigorous simulation models with ASPEN PIMS.

Working Environment

Our high-performing employees are attracted by the challenging and rewarding opportunities we offer and are compensated accordingly.


At Aramco, our people work on world-scale projects supported by unmatched investment in capital and technology. We heavily invest in talent development to address major technical, logistical, and environmental challenges, with extensive workforce training programs.


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To apply, please visit the following URL:

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