Technical Product Manager, ML & Robotics

Mariana Minerals is a software-first, vertically integrated minerals company supplying critical minerals for modern energy, AI, and defense technologies. The Technical Product Manager will be the single product owner for machine learning and industrial robotics, including the ML platform, the simulators it runs, and the perception and robotics initiatives built on it, and will own the seam between the applied AI/ML organization and the software engineering organization. The role focuses on setting direction, aligning stakeholders, and keeping engineers focused on high-impact technical work, with the goal of moving ML systems from ad hoc experimentation into supported software for autonomous industrial process and chemical operations.

Responsibilities

Talk to internal teams (operators, process engineers, and MLEs) to set the roadmap; Own the roadmap for the ML platform; Write product specs, KPIs, and success metrics that turn ML and autonomy asks into scoped, shippable work; Own prioritization and stakeholder alignment so MLEs stay focused on deep technical work; Own the path to process autonomy and the simulators that underpin it; Own the roadmap for vision, sensor, and robotics initiatives; Own the seam between the applied AI/ML org and the software engineering org, and the boundary with MarianaOS; Define what it takes for a model, simulator, or robot to be trusted in production and be explicit about which initiatives won't be pursued

Requirements

4–8+ years in technical product management, ML platform or robotics product roles, or equivalent experience leading cross-disciplinary technical programs; Comfortable being the only PM in a highly technical room; Enough depth in ML systems (training, evaluation, deployment, perception, simulation) to earn credibility with ML engineers and software engineers; Track record of bringing structure to ambiguous, cross-functional initiatives; Strong prioritization and tradeoff skills; Exceptional written and verbal communication across audiences; Nice to have: product ownership of an ML platform, MLOps stack, or simulation system in production; Prior work on industrial robotics, perception, or closed-loop optimization of chemical or industrial process systems; Familiarity with process simulation toolchains (SysCAD or similar); Background in mining, energy, chemicals, manufacturing, or other heavy industry; Working fluency with the current LLM/foundation-model landscape

Nice to have

Product ownership of an ML platform, MLOps stack, or simulation system in production; Prior work on industrial robotics, perception, or closed-loop optimization of chemical or industrial process systems; Familiarity with process simulation toolchains (SysCAD or similar); Background in mining, energy, chemicals, manufacturing, or other heavy industry, especially industrial automation or sensor/vision data; Working fluency with the current LLM/foundation-model landscape and where it applies to ML and robotics workflows