Machine Learning Engineer – PINN / FNO & Reservoir Simulation

Join CMG’s Innovation Lab asMachine Learning Engineer with a Master’s or PhD focused on Physics-Informed Neural Networks (PINNs), Fourier Neural Operators (FNOs), Deep Reinforcement Learning (DRL) for reservoir and CFD applications. In this role you’ll blend advanced ML theory with practical reservoir modeling, driving accuracy and performance improvements from concept through production.

Key Responsibilities

Simulation & ML Integration :

• Design and implement PINN-based solvers, FNO surrogates or others to accelerate reservoir simulation and optimize subsurface workflows.
• Integrate your models into CMG’s simulation pipeline, ensuring numerical stability and scientific rigor.
• Build scalable data pipelines for large-scale geological and production datasets.
• Containerize and deploy inference services, wrapping PINN / FNO models with robust APIs.

Strategic Roadmap :

Early-Stage Research & Delivery :

Cross-Functional Collaboration :

The above statements are intended only to describe the general nature of the job and should not be construed as an all-inclusive list of position responsibilities.

Knowledge, Skills & Experience

Academic Excellence :

Deep ML & Scientific Computing :

Software & DevOps Skills :

Analytical & Problem-Solving :

Teamwork & Communication :

If you have the necessary qualifications, and are interested in a challenging career with us, please forward your resume in confidence to resumes@cmgl.ca .

No phone calls please. We thank all applicants for their interest in advance. Only those chosen for interviews will be contacted.

CMG Compensation and Benefits Overview

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