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Machine Learning Engineer @ Mariana Minerals

Marianaminerals

San Francisco, CAOn-siteFull-time$140k – $220k / year

About this role

Machine Learning Engineer @ Mariana Minerals - Back to Mariana Minerals’s Job Listings Machine Learning Engineer Location Ann Arbor, MI; Houston, TX; San Francisco HQ Employment Type Full time Location Type On-site Department Software Development Compensation - Estimated Base Salary, final salary based on experience, location, and other factors $120K – $180K • Offers Equity About Mariana Minerals Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We’re reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making. The Role Mariana Minerals is building the critical minerals supply chain from the ground up—and we're looking for Machine Learning Engineers to help make it autonomous. We're not a software company selling tools to mining operators. We are a mining company that builds software. Mariana designs, builds, commissions, and operates our own mines and refineries. We develop proprietary chemical processes and run them at lab, pilot, and commercial scale. 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. As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning systems that control our mineral refining facilities. You'll start with well-scoped problems inside our simulators and training pipelines—and ramp quickly toward owning models that run on real, operating plants. Your work won't live behind dashboards or proxy metrics; you'll see its impact in real recovery rates, energy consumption, reagent usage, and uptime. The Tech This is some of the most interesting applied AI work happening today. Our internal platform us

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