Senior Geo Data Scientist - VRIFY

VRIFY is positioned at the forefront of the mining industry's transformation, leveraging cutting-edge AI to revolutionize mineral exploration. With a focus on AI drill targeting, VRIFY is expanding its capabilities by synthesizing vast amounts of geological information. This integration enhances the precision and efficiency of exploration strategies, offering our clients innovative solutions that depart from traditional methods.

Our mission extends beyond technological advancement. We are committed to transforming how mining companies engage with investors, aiming to foster a more transparent and accountable mining investment ecosystem. VRIFY 's technology enables immersive 3D and 360° presentations that provide investors with a vivid and detailed visual context, making complex geological data accessible and engaging.

As we continue to refine our AI-driven solutions, VRIFY remains dedicated to driving innovation and excellence in the mining sector, ensuring our clients and investors are well-equipped to succeed in a rapidly evolving market.

The Role

You'll build the ML systems that turn complex geospatial data into actionable predictions for mineral exploration — from ingestion and feature engineering through deployment, monitoring, and reliability. You'll work on high-dimensional spatial datasets, productionize models, and bring modern AI (Vision Transformers, GNNs, Hugging Face, Earth Engine) into our pipelines.

This is a senior IC role on a small, high-trust team. We're looking for someone who operates independently, communicates consistently, and is genuinely curious about the mining domain. Remote-first within Canada, with consistent availability during business hours.

What You'll Do

• Design and deploy ML models for geospatial applications, including Vision Transformers and GNNs on high-dimensional raster and spatial datasets.
• Build scalable, automated data pipelines — preprocessing, feature engineering, sampling, and spatial cross-validation.
• Own end-to-end ML workflows: scheduling, monitoring, alerting, retraining, and reliability.
• Develop custom geospatial models and features that capture real-world spatial patterns.
• Apply model interpretability techniques to understand spatial patterns and feature influence.
• Use Google Earth Engine, Hugging Face, and similar tools to scale geospatial AI in production.

Must-Haves

• BSc, MSc, or PhD in Computer Science, Engineering, Geoscience, or related field (or equivalent practical experience).
• 5+ years in ML, data science, or software development, including production ML systems.
• Strong Python and modern ML frameworks (PyTorch, TensorFlow, JAX, scikit-learn).
• Deep understanding of ML architectures (transformers, vision transformers, clustering, ensembles).
• Experience applying deep learning (Vision Transformers,