Marianaminerals

Marianaminerals

Machine Learning Engineer

Ann Arbor, MI · Senior

Sponsorship not specifiedDetected 41 days ago
PythonMachine LearningDeep LearningSupply ChainResearch

About the role

  • We're not a software company selling tools to mining operators.
  • Today, we're producing battery-grade lithium salts from real oil and gas wastewater in our facilities.
  • Our first commercial-scale lithium production facility, Lithium One, is targeting initial production in Q1 of 2027.

Responsibilities

  • Build and refine pieces of our training environments-reward functions, observations, and action logic-with guidance from senior engineers.
  • Partner with process and chemistry experts to understand the unit operations you're modeling.
  • We own the projects, generate the data, and close the loop.

Requirements

  • When you ship here, you can literally watch the physics change.
  • Proficiency in Python and comfort reading and debugging an existing codebase.
  • 0-4 years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing-or a strong recent graduate with demonstrated project depth.
  • Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning; exposure to reinforcement learning is a strong plus.
  • Curiosity about physical, industrial systems and eagerness to learn chemistry and process engineering from experts who will challenge your assumptions.
  • A self-starter who asks good questions, ships, and escalates blockers early.

Benefits

  • Run reinforcement learning experiments in our physically realistic simulators of mineral processing operations, and help turn the results into better controllers.
  • Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning
  • exposure to reinforcement learning is a strong plus.

Company info

  • We are a mining company that builds software.

This listing is sourced directly from Marianaminerals's careers page and normalized into a canonical job model.