Technical Product Manager, ML & Robotics

Mariana Minerals is building machine learning and industrial robotics to support safer, more reliable autonomy in heavy industry. In this Technical Product Manager role, you will serve as the single product owner for the ML platform and the robotics initiatives around it, setting direction for trusted production deployment and defining what “good enough” means for real-world systems.

Based in San Francisco, CA (onsite), you will translate ambiguous requests across ML, perception, simulation, and engineering into scoped work that ships, with clear prioritization and explicit decisions about what will not be pursued.

What you’ll own

• Continuous collaboration with internal teams, where operators, process engineers, and MLEs function as your primary users and their problems set the roadmap.
• The roadmap for the ML platform, including the next capabilities to build, the use cases to target, and the rationale behind sequencing.
• Product specifications, KPIs, and success metrics that convert ML and autonomy needs into shippable, well-scoped outcomes.
• Prioritization and stakeholder alignment that keeps MLEs focused on deep technical work.
• The path to process autonomy, covering models that increasingly inform and set process and chemical operating decisions, supported by simulators.
• The roadmap for vision, sensor, and robotics initiatives, including which plant problems receive the first model or robot and how “trusted enough to deploy” is determined per initiative.
• The seam between the applied AI/ML organization and the software engineering organization, including the boundary with MarianaOS, so no work is lost between orgs.
• Definition of the criteria required for a model, simulator, or robot to be trusted in production, including initiatives that will not be pursued.

How you’ll operate

• Structure from ambiguity: bring direction to cross-disciplinary initiatives and align stakeholders without waiting for direction.
• Ruthless, visible prioritization: be explicit about what will not be worked on, not only what is planned.
• Hybrid Pioneer/Settler approach: prioritize and ship lightweight demos on ambiguous problems while adding structure to existing work streams that lack cohesive ownership.
• Ecosystem fluency: understand the Mariana ML, perception, and robotics ecosystem as a whole, including where it sits relative to the current frontier of model capability, to keep prioritization well-calibrated.

What you bring

• 4–8+ years of technical product management, ML platform or robotics product experience, or equivalent experience leading cross-disciplinary technical programs.
• Comfort operating as the only PM in a highly technical environment, including knowing when to drive decisions, when to defer to engineers, and how to build credibility.
• Enough depth in ML systems across training, evaluation, deployment, perception, and simulation to earn credibility with both ML and software engineers and to judge which technical answers hold.
• A track record of bringing structure to ambiguous, cross-functional initiatives, including setting direction, aligning stakeholders, and owning outcomes end-to-end.
• Strong prioritization and tradeoff skills, including the ability to say no visibly.
• Exceptional written and verbal communication across audiences, from ML engineers to operators to executives.

Nice to have

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

Culture

• Everyone Gets Home Safe. We never put speed or cost ahead of people.
• Extreme Ownership. We take full responsibility for outcomes, relentlessly driving toward solutions.
• Engineer Out Requirements, then Automate. We simplify, optimize, and then automate for scale.
• Share Your Legos. We collaborate openly, share knowledge, and empower each other to build bigger, better solutions.

Compensation

USD $115,000 - $208,000 per year