Staff Machine Learning Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Staff Machine Learning Engineer Ann Arbor, MI, Ann Arbor, Michigan, United States 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 a Staff Machine Learning Engineer 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 Staff Machine Learning Engineer at Mariana, you'll set the technical direction for how we make refining autonomous. You'll define how control models are built, validated, and trusted on live equipment across our circuits and facilities-and you'll personally take on the hardest modeling problems standing between us and fully autonomous operations. Your decisions will show up in real recovery rates, energy consumption, reagent usage, and uptime across every plant we run. The Tech This is some of the most interesting applied AI work happening today. Our internal platform, uses the

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