• Artificial Intelligence Engineer

    Schlumberger (Houston, TX)


    Build, train and deploy large-scale, self-supervised “foundation” models that learn rich representations of seismic data (ND(2D,3D,…) volumes), to be fine-tuned for tasks such as event detection, subsurface imaging, fault characterization or reservoir property estimation.

     

    + Domain Knowledge

    + Seismic theory & processing: data formats (SEG-Y/D), de-noising, deconvolution, stacking, migration, tomography, inversion.

    + Reservoir geomechanics, rock physics, well-log integration, AVO/AVA analysis.

    + Geostatistics: variography, kriging, co-kriging, uncertainty quantification.

    + Machine-Learning & Foundation-Model Expertise

    + Self-supervised and semi-supervised learning: masked autoencoders (MAE), contrastive methods (SimCLR, BYOL), clustering-based (DINO), predictive coding.

    + Model architectures: 1D/2D/3D CNNs, Vision/Audio Transformers, graph neural networks, diffusion/generative models, multi-modal encoders.

    + Transfer learning & fine-tuning at scale: prompt/adapter-based techniques, domain adaptation.

    + Evaluation metrics: geophysical error norms (L2, semblance), detection/segmentation metrics (IoU, F1), end-use KPIs (horizon-picking accuracy, attribute classification).

    + Software & Infrastructure

    + Programming: expert Python (NumPy, SciPy, Pandas), C++/CUDA for performance kernels.

    + Deep-learning frameworks: PyTorch (Lightning, Distributed), TensorFlow/Keras, JAX/Flax.

    + Large-scale training: multi-GPU, multi-node, mixed-precision, ZeRO optimization.

    + Data engineering: advanced segmentation of terabyte-scale seismic volumes.

    + Mathematical & Algorithmic Foundations

    + Linear algebra, probability & statistics, optimization (stochastic, convex, non-convex).

    + Signal processing: Fourier/Wavelet transforms, filtering, spectral analysis.

    + Numerical methods for PDEs, inverse problems, regularization techniques.

    + Collaboration & Communication

    + Cross-disciplinary teamwork with geoscientists, software engineers, product managers and end-users.

    + Clear presentation of complex model behaviors, uncertainty quantification and business impact.

    + Desired Extras

    + Contributions to open-source seismic/ML projects or standards bodies (e.g. SEG, OSDU).

    + Cloud & DevOps: AWS/GCP/Azure (S3, EC2/GPU, Batch/ML Engine), Kubernetes, Terraform, Docker, CI/CD pipelines.

    + Experiment tracking & MLOps: MLflow, Weights & Biases, Neptune, Grafana, Prometheus.

    + Multi-modal fusion: combining seismic with well logs, production data, satellite/inSAR.

    + Agile/Scrum practices: sprint planning, peer code reviews, documentation (API specs, best practices).

    + Education & Experience

    + PhD (or M.S. + 5+ years) in Geophysics, Seismology, Computer Science, Electrical Engineering, Applied Math, or equivalent.

    + 2–3+ years hands-on seismic/geophysical data processing or interpretation.

    + Peer-reviewed publications or patents in seismic AI, geophysical inversion or related fields a plus.

     

    Company policy is to provide every individual a fair and equal opportunity to seek employment and advancement at the Company without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, citizenship, genetic information, veteran or military status, disability, creed, ancestry, pregnancy (including pregnancy, childbirth and related medical conditions), marital status or any factors protected by federal, state, or local laws. We are an “Equal Opportunity Employer". For more information please, refer to the latest version of "Know Your Rights" poster and the "Pay Transparency Nondiscrimination Poster" located here: https://www.dol.gov/agencies/ofccp/posters. The Company is a VEVRAA Federal Contractor - priority referral Protected Veterans requested.