Job Description

Role Overview
Mariana Minerals is looking for a highly motivated Machine Learning Engineer to work on building the critical minerals supply chain.
As a Machine Learning Engineer at Mariana Minerals, you will lead the development and deployment of ML models to control the operation of Mariana’s mineral refining facilities and apply LLMs to accelerate the engineering and construction of physical infrastructure that is critical to the minerals supply chain. Responsibilities will include developing and training ML models of the various chemical operations in Mariana’s mineral processing facilities, training and deploying RL models to control the operations of Mariana’s mineral processing facilities (no robotics required), building data preprocessing, training, and validation pipelines, and applying LLMs to parse unstructured data to assist Mariana’s internal engineering and construction teams.
What You’ll Do
Work closely with Mariana’s internal process chemistry teams to develop novel data driven models of key chemical unit operations.
Use data from physically realistic simulators to pretrain RL control algorithms and work with subject matter experts to debug and understand gaps between expected model performance and actual performance.
Work with Mariana’s internal teams to incorporate data from inline sensors and instruments to improve model performance.
Work closely with Mariana’s software engineers to implement novel LLM powered experiences that assist Mariana’s internal teams.
Assist with the data architecture for Mariana’s data pipelines to feed the training of novel ML models that control Mariana’s mineral processing facilities and provide visibility into the operation of the facilities to the internal Mariana team.
What You’ll Bring
Strong understanding of ML fundamentals and ability to incorporate ideas from research into novel production applications.
Demonstrated ability to develop and deploy ML models in production settings (2+ years preferred).
Self-starter mindset, ability to bring clarity to high ambiguity situations, and excitement to work with subject matters experts in mechanical, chemical, and process engineering.
Ability to work across the entire stack from data pipelines to model inference and monitoring and everything in between (or demonstrated proficiency in one of these areas and the desire to expand your skillset).
Compensation Range: $140K - $190K

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