Forward Deployed Machine Learning Engineer

StratumAI; Deutschland; Remote; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A leading AI solutions company is seeking a Forward Deployed Engineer to apply deep learning solutions in mining operations. The ideal candidate has strong ML expertise and proficiency in PyTorch, along with excellent communication skills. This remote-first role allows for significant impact in improving modeling techniques and requires 2+ years of industry experience.

Qualifikationen

• 2+ years of industry machine learning experience.
• Strong proficiency in implementing custom neural networks in PyTorch.
• Excellent communication skills - able to explain complex concepts to non-technical people.

Aufgaben

• Apply and refine deep learning models to specific mine sites.
• Develop and maintain high-quality machine learning code using Python and PyTorch.
• Communicate model quality and performance to non-ML technical stakeholders.

Kenntnisse

Custom neural network architectures

Data analysis and visualization

Communication skills

Self-driven problem solving

Tools

Python

PyTorch

Jobbeschreibung

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