About the job
Join Stratum AI as a Forward Deployed Machine Learning Engineer and be part of our Technical Services team focused on tackling complex real-world challenges.
In this role, you will work extensively with custom architectures using PyTorch, applying your expert knowledge of complex Convolutional Neural Networks, Graph Neural Networks, and Transformers.
We prefer candidates based in Canada for this remote-first position.
Technical Services Team Responsibilities
Conduct foundational research to design and implement advanced AI resource modeling techniques applicable to various mining operations.
Refine existing architectures to train resource models tailored for specific mines.
Effectively communicate model quality, metrics, performance, and methodologies to non-ML technical stakeholders.
Identify opportunities for enhancing mining operations and garner client support for new modeling parameters.
Monitor deployed model performance over time and innovate on ways to improve existing models.
Role Responsibilities
Customize Stratum’s deep learning models for specific mining contexts.
Develop and sustain high-quality machine learning code using Python.
Explore innovative approaches to enhance resource and metallurgical models for specific mines.
Allocate 60% of your time to applied ML for individual mines and 40% to foundational ML across multiple mines.
Participate in a minimum of 2 mine visits annually to engage directly with clients.
Develop into a senior engineer capable of identifying additional applications of our technology with existing clients.
Navigate and thrive amidst complex datasets and evolving client needs, turning ambiguity into structured, actionable plans.
Role Requirements
Minimum of 2 years of experience in machine learning or related fields.
Proficient in Python and PyTorch with a strong foundation in deep learning principles.
Experience with Convolutional Neural Networks, Graph Neural Networks, and Transformers is essential.
Excellent communication skills, particularly in translating technical concepts to non-technical audiences.
Strong analytical and problem-solving abilities, especially in ambiguous situations.

