Applied ML Engineer for Autonomous Mineral Refining

Talentify; Houston (TX); On-site; USD 140,000 - 200,000; Full time

Job summary

Mariana Minerals is building autonomous mineral refining systems and is seeking a Machine Learning Engineer to advance RL controllers that operate real plants. You will train models in realistic simulators, then close the gap with live data to improve recovery, energy use, and uptime.

You'll work at the intersection of software and chemical engineering, collaborating with process and chemistry experts to translate physics into reliable, scalable automation.

Qualifications

• 2–8+ years of experience in ML, RL, or scientific computing, or a strong recent graduate with project depth.
• Solid grounding in ML with deep learning and RL exposure.
• Proficiency in Python and reading existing codebases.
• Curiosity about physical industrial systems and willingness to learn chemistry/process engineering.
• Self-starter with initiative to ship and raise blockers early.

Responsibilities

• Run reinforcement learning experiments in simulators of mineral processing, and help turn results into better controllers.
• Build and refine training environments—reward functions, observations, and action logic—with guidance from senior engineers.
• Train control models, track and interpret performance, and analyze when a model underperforms.
• Bridge simulation results with real plant data and flag where the physics diverges.
• Write clean, well-tested code and contribute to services that put models into production.
• Collaborate with process and chemistry experts to model unit operations.

Skills

Machine learning

Reinforcement learning

Scientific computing

Python

Job description

Mariana Minerals is building autonomous mineral refining systems and is seeking a Machine Learning Engineer to advance RL controllers that operate real plants. You will train models in realistic simulators, then close the gap with live data to improve recovery, energy use, and uptime.

You'll work at the intersection of software and chemical engineering, collaborating with process and chemistry experts to translate physics into reliable, scalable automation.