Join Our Innovation Lab as a Machine Learning Engineer At CMG, we believe that people are our most valuable asset. As a Machine Learning Engineer in our Innovation Lab, you will work alongside a talented team to develop cutting-edge AI and ML solutions for reservoir simulation. If you have 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, we want to hear from you. Key Responsibilities: - Simulation & ML Integration: - Design and implement PINN-based solvers, FNO surrogates, or other models to accelerate reservoir simulation and optimize subsurface workflows. - Integrate your models into CMG's simulation pipeline, ensuring numerical stability and scientific rigor. - Data & Pipeline Engineering: - 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: - Collaborate with domain experts to define a multi-year ML/AI strategy for reservoir simulation. - Identify key research areas and drive prototyping of next-generation ML solvers. - Early-Stage Research & Delivery: - Lead R&D; projects—from literature review and algorithm design through hands-on implementation and performance benchmarking. - Validate model accuracy against high-fidelity simulators and real field data. - Cross-Functional Collaboration: - Pair with software engineers to productionize algorithms under clean-architecture and CI/CD best practices. - Present findings, trade-offs, and performance metrics to stakeholders in product and subsurface teams. We're looking for individuals who share our passion for innovation and problem-solving. If you're excited about the opportunity to join our team and contribute to the development of cutting-edge AI and ML solutions, please submit your application.