Technical Product Manager, ML & Robotics at Mariana Minerals in San Francisco HQ

Job description

• Application
• Mariana Minerals is a software-first, vertically integrated minerals company supplying the minerals critical to modern energy, AI, and defense technologies. Our ML systems don't live in a vacuum — they run chemistry and process simulators, see and act in our plants through sensors and robotic systems, and increasingly move toward autonomous industrial process and chemical operations.
• We're hiring a Technical Product Manager to be the single product owner for machine learning and industrial robotics — the ML platform, the simulators it runs, and the perception and robotics initiatives built on it — and to own the seam between our applied AI/ML organization and our software engineering organization. Today this work is split across technical leads with no one setting direction across the whole. Your job is to change that: decide what the ML organization pursues and why, get stakeholders aligned behind it, and make sure engineers can stay heads-down on the work that matters.
• Autonomy and robotics here mean industrial: models, perception systems, and robotic hardware that increasingly close the loop on how our plants and chemical processes run.

Responsibilities

• Talk to our internal teams constantly — operators, process engineers, and MLEs are your users, and their problems set the roadmap.
• Own the roadmap for the ML platform: which capabilities it needs next, for which use cases, and why.
• Write the product specs, KPIs, and success metrics that turn ambiguous 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 — models that inform, and increasingly set, process and chemical operating decisions — and the simulators that underpin it.
• Own the roadmap for vision, sensor, and robotics initiatives: which plant problems get a model or a robot first, and what "good enough to deploy" means for each.
• Own the seam between the applied AI/ML org and the software engineering org, and the boundary with MarianaOS, so nothing falls in the gap.
• 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

• Must have
• 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 — you know when to drive a decision, when to defer to engineers, and how to build credibility without being the most technical person there
• Enough depth in ML systems — training, evaluation, deployment, perception, simulation — to earn credibility with both ML engineers and software engineers, and to know when a technical answer is a good one
• Track record of bringing structure to ambiguous, cross-functional initiatives: setting direction, aligning stakeholders, and owning outcomes end-to-end
• Strong prioritization and tradeoff skills — you know when to say no, and you say it visibly
• Exceptional written and verbal communication across audiences, from ML engineers to operators to executives
• 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

Skills

Required

• Technical product management
• Prioritization and tradeoff skills
• Stakeholder alignment
• Structuring ambiguous initiatives