Forward Deployed Machine Learning Engineer

The role

This person will adapt deep learning models to specific mines and develop machine learning code using Python. The role involves 60% applied ML for specific mines and 40% foundational ML for mines in general.

What you will do

• Adapt Stratum's deep learning models to a given mine
• Develop and maintain high-quality machine learning code using Python
• Create better resource and metallurgical models with deep learning
• Take part in at least 2 mine visits a year and engage with clients on the ground
• Conduct foundational research to design and implement AI resource modeling techniques
• Apply and refine existing architecture to train resource models for a specific mine
• Communicate model quality, metrics, performance, and methodology to non-ML technical external stakeholders
• Identify new opportunities to improve mining operations for a given client
• Track model performance of deployed models over time
• Grow into a senior engineer who can identify additional ways technology can be leveraged

Required qualifications

• 2+ years of industry machine learning experience
• Excellent proficiency in implementation of custom neural network architectures in Python (Pytorch)
• 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)

Nice to have

• Ability to speak another language with high proficiency
• Hands-on experience with various neural network types

About the company

Stratum is a mining software company with machine learning models as its core product. The company uses 3D maps to predict mineral distribution using proprietary ML protocols.