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Mariana Minerals is a software-first, vertically integrated minerals company supplying critical minerals for modern energy, AI, and defense technologies. The company combines deep industry expertise with advanced software, automation, and data-driven decision-making to reimagine the minerals supply chain.
You will be the single product owner for machine learning and industrial robotics at Mariana, owning the ML platform, the simulators it runs, and the perception and robotics initiatives built on it. You will own the seam between the applied AI/ML organization and the software engineering organization. Currently this work is split across technical leads with no unified direction; your role is to consolidate ownership, set strategic direction, align stakeholders, and enable engineers to focus on high-impact work.
Key responsibilities include:
- Constantly engage with internal teams (operators, process engineers, ML engineers) to understand their problems and set the roadmap
- Own the ML platform roadmap: determine which capabilities are needed next, for which use cases, and the rationale
- Write product specs, KPIs, and success metrics that translate ambiguous ML and autonomy requests into scoped, shippable work
- Drive prioritization and stakeholder alignment so ML engineers can focus on deep technical work
- Own the path to process autonomy—models that inform and increasingly control process and chemical operating decisions—and the simulators that support it
- Own the roadmap for vision, sensor, and robotics initiatives: decide which plant problems get a model or robot first, and define "good enough to deploy"
- Bridge the gap between the applied AI/ML organization and software engineering, including boundaries with MarianaOS
- Define production readiness criteria for models, simulators, and robots; be explicit about which initiatives won't be pursued
You will operate by bringing structure from ambiguity, making ruthless and visible prioritization decisions, balancing lightweight demos on ambiguous problems with structured ownership of existing work streams, and maintaining ecosystem fluency across ML, perception, and robotics to keep prioritization well-calibrated.
REQUIREMENTS:
Must have:
- 4–8+ years in technical product management, ML platform or robotics product roles, or equivalent experience leading cross-disciplinary technical programs
- Comfort being the only PM in a highly technical room; ability to know when to drive decisions, when to defer to engineers, and how to build credibility without being the most technical person present
- Sufficient depth in ML systems (training, evaluation, deployment, perception, simulation) to earn credibility with both ML engineers and software engineers, and to recognize when a technical answer is sound
- 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; ability to say no visibly and clearly
- Exceptional written and verbal communication across audiences (ML engineers, operators, executives)
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 (e.g., SysCAD)
- 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 its applications to ML and robotics workflows
