Forward Deployed Machine Learning Engineer

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August 8

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Stratum AI

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Artificial Intelligence • Mining • B2B

Stratum AI is reimagining mining with its advanced AI-driven technology that creates more accurate models for mine planning and grade control through Machine Learning. Their innovations enable increased average mined grade by distinguishing between ore and waste more effectively and improving the realized net present value (NPV) of mine plans. Stratum AI's dynamic reconciliation technology tracks ore in real-time, allowing for efficient error correction and enhanced drill targeting, thereby leading to reduced waste and optimized resource extraction.

11 - 50 employees

Founded 2018

🤖 Artificial Intelligence

🤝 B2B

📋 Description

• We are looking for a Forward Deployed ML Engineer, with an interest in solving difficult real-world problems to join our Technical Services team. • This role will require extensive working with custom architectures on PyTorch. • Previous experience working with PyTorch on complex Convolutional Neural Network, Graph Neural Network, and/or Transformers is expected. • This is a remote-first position, with a preference for applicants based in Canada. • Conducting foundational research to design and implement more accurate AI resource modeling techniques that we can use for many different mining operations. • Applying and refining existing architecture to train resource models for a specific mine. • Communicating the quality, metrics, performance, and methodology of our models to non-ML technical external stakeholders. • Identifying new opportunities to improve mining operations (such as modelling other parameters) for a given client and getting their support in doing so. • Tracking model performance of deployed models over time and identifying ways to make existing models better. • Adapt Stratum’s deep learning models to a given mine. • Develop and maintain high-quality machine learning code using Python. • Unlock ways to create better resource and metallurgical models with deep learning for one specific mine, or sometimes mines in general • 60% of your time is dedicated to applying ML to one specific mine (applied ML), 40% is dedicated to applying ML to mines in general (foundational ML). • Take part in at least 2 mine visits a year and engage with our clients on the ground. • Over time, grow into a senior engineer who can identify additional ways our technology can be leveraged with our existing clientele.

🎯 Requirements

• 2+ years of industry machine learning experience. • Excellent proficiency in implementation of custom neural network architectures in Python (Pytorch). • The ideal candidate will have hands-on experience with various neural network types • Strong foundational knowledge of deep learning with an emphasis on transformers, convolutional neural networks, and/or graph neural networks. • Adept at working with a high degree of autonomy and initiative to solve complex problems. • Strong technical communication skills (oral + visual). • You will be responsible for conveying to other non-machine learning engineers in the mining industry why our models are good. You will work with geologists and business development roles to tell the story. • Ability to speak another language with high proficiency.