Staff Machine Learning Engineer
About Mariana Minerals
Mariana Minerals is a software-first, vertically integrated minerals company focused on supplying critical minerals essential for modern energy, AI, and defense technologies. We aim to revolutionize the minerals supply chain by integrating advanced software, automation, and data-driven decision-making with deep industry expertise.
The Role
Mariana Minerals is pioneering the critical minerals supply chain and seeks a Staff Machine Learning Engineer to drive its autonomy. Unlike traditional software companies, we are a mining company that develops and operates our own mines and refineries. Our first commercial-scale lithium production facility, Lithium One, is scheduled to start production in Q1 2027. As a Staff Machine Learning Engineer, you will lead the development of autonomous refining operations by defining and validating control models that optimize recovery rates, energy consumption, reagent usage, and uptime across all our facilities.
Tech
This role involves cutting-edge applied AI work, particularly in the realm of autonomous mineral refining. Our platform uses reinforcement learning toolkits similar to those used in self-driving cars and humanoid robots, but tailored for real-time control of refining circuits. The environment is dynamic and non-stationary, requiring continuous adaptation and optimization across multiple objectives.
What You’ll Do
Own the autonomy roadmap across multiple circuits and facilities, deciding which unit operations to automate next and where investments in simulation and modeling are most effective.
Define how control models are validated and certified for deployment on real refining equipment, including methods for measuring and closing the gap between simulation and real-world performance.
Set the standards for our simulators and modeling stack, ensuring reproducibility, safety, and alignment with real-world economics.
Solve the hardest modeling and control problems, such as non-stationarity, safety constraints, and multi-objective optimization across recovery, reagent use, energy, and uptime.
Partner with leadership on major capital and operational decisions, translating techno-economic insights into strategic direction.
Multiply the team through technical direction, design reviews, and mentoring of engineers at all levels.
Collaborate with data engineering leaders to shape the data platform required for the autonomy roadmap.
Desired Qualifications
8+ years in machine learning engineering (or 6+ with exceptional org-level technical leadership), including experience in production ML or control systems.
A proven track record of setting technical direction for ML systems in physical, industrial, robotics, or control domains.
Deep expertise in reinforcement learning under non-stationarity, simulation and digital twins, and methods for closing the sim-to-real gap.
Demonstrated ability to de-risk ambiguous, never-before-done problems, framing objectives, success metrics, and paths for others.
Strong cross-functional influence with technical leadership and domain experts, including chemists, metallurgists, process engineers, and geologists.
A builder at heart, with a history of shipping technical solutions.
Why This Role
This role offers the opportunity to set the technical direction of an entire industrial-AI platform as it's being developed, rather than maintaining one that already exists. Our culture emphasizes Extreme Ownership, Engineer Out Requirements, and Share Your Legos, fostering collaboration and innovation.
Career Path
We offer a competitive compensation range of $160K - $200K, reflecting the significant impact and potential of this role in shaping the future of responsible mineral sourcing and supply.