Forward Deployed Machine Learning Engineer

StratumAI; United States; Remote; USD 80,000 - 120,000; Full time

Job summary

An innovative company is seeking a self-driven Forward Deployed Engineer to join their Core AI team. This role focuses on applying advanced deep learning solutions to enhance mining operations while also contributing to foundational research. The ideal candidate will have strong expertise in custom neural network architectures, particularly in PyTorch, and will be responsible for training models, developing data processing pipelines, and communicating complex concepts to non-technical stakeholders. This remote-first position offers a unique opportunity to make a significant impact in the mining industry through cutting-edge AI technology.

Qualifications

• 2+ years of industry machine learning experience.
• Strong proficiency in implementing custom neural networks.

Responsibilities

• Apply and refine deep learning models to mining operations.
• Develop and maintain high-quality machine learning code.

Skills

Machine Learning

PyTorch

Data Preprocessing

Data Visualization

Communication Skills

Problem Solving

Education

Bachelor's Degree in Computer Science or related field

Tools

Python

Job description

We are looking for a self-driven Forward Deployed Engineer with strong ML expertise to join our Core AI team. This role focuses on applying our deep learning solutions to specific mining operations while also contributing to foundational research that improves our modeling techniques across all mine sites.

This position requires extensive experience with custom neural network architectures in PyTorch. This is a remote-first position, with a preference for applicants based in Canada.

Key Responsibilities

• Apply and refine StratumAI's deep learning models to specific mine sites:

  • Train models on mining operation data

  • Implement proper data preprocessing for mining datasets

• Develop and maintain high-quality machine learning code using Python and PyTorch:

  • Implement custom ML architectures

  • Create data processing pipelines specific to mining operations

  • Develop evaluation code to assess model performance against industry-relevant metrics

• Create and optimize AI resource and metallurgical models:

  • Produce block models from processed data

  • Compare against traditional industry standard methods

• Communicate model quality, performance, and methodology to non-ML technical stakeholders:

  • Present visualization of model performance to geologists and business teams

  • Explain technical concepts to mining professionals

• Track model performance over time:

  • Monitor model predictions across different time periods

  • Analyze model behavior with different noise patterns

  • Implement techniques to combat data drift and bias

• Identify new applications of our technology for existing clients

• Split time between applied ML (60% - focused on specific mine sites) and foundational ML research (40% - applicable across multiple sites)

Requirements

• 2+ years of industry machine learning experience

• Strong proficiency implementing custom neural networks in PyTorch

• Experience analyzing and visualizing data

• Ability to preprocess spatial and temporal data

• Excellent communication skills - able to explain complex concepts to non-technical people

• Self-driven problem solver who can work autonomously

Nice to Have

• Mining industry experience or geospatial data experience

• Background in resource modeling or geological sciences