Product Manager, PlantOS

About Mariana Minerals

Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies.

We’re reimagining how minerals are sourced, refined, and optimized by combining deep industrial expertise with software, automation, and data-driven decision-making. Join us as we build the future of responsible mineral sourcing and supply.

We're looking for a Product Manager to own Plant

OS—the platform that enables Mariana to operate processing facilities at a level of efficiency and consistency that traditional operators can't match.

This role sits at the intersection of process engineering, machine learning, and product development. You'll work with chemical engineers, metallurgists, ML engineers, and plant operators to understand how mineral processing actually works—and where software can make it work better. You'll translate complex process requirements into product decisions, and ship software that runs in production environments where mistakes have real consequences.

You'll need strong communication skills to bridge very different disciplines: the operators who run the plant, the process engineers who design it, and the ML engineers who build the models. You'll need to be comfortable with technical depth while maintaining focus on user needs and business outcomes.

Plant

OS is Mariana's autonomy platform for fixed-plant mineral processing. It's the system that controls and optimizes everything that happens inside a processing facility—lithium refining, solvent extraction and electrowinning (SX-EW), grinding, flotation, and beyond.

• Exposes all the information (everything from design drawings to PLC data) needed to manage a facility in one easy to navigate location – and directs operator attention to the most relevant metrics to drive continuous improvement
• Uses reinforcement learning to dynamically adjust operating conditions in real-time, responding to feed variability and process upsets
• Optimizes recovery, throughput, energy consumption, and reagent usage simultaneously across different process types
• Accelerates facility ramp-up by encoding operational expertise into software
• Moves toward no‑human‑in‑the‑loop operations for routine process control

Mineral processing is a complex dance of chemistry and physics—dozens of interdependent variables where small adjustments compound into major differences in yield, quality, and cost. Plant

OS is how we run processing facilities smarter than anyone else.

• Own the Plant
  
  OS roadmap
  :
  Define what we build, in what order, based on operational needs and business impact
• Stakeholder management
  :
  Build relationships with plant operators, process engineers, metallurgists, and ML engineers—translate between their different worldviews
• Cross‑functional delivery
  :
  Partner with software and ML teams to ship control systems that work reliably in production
• User research
  :
  Spend time at processing facilities understanding how operators make decisions, where they struggle, and what information they need
• Process optimization
  :
  Work with domain experts to identify where ML‑driven control can improve recovery, throughput, or efficiency
• Safety and reliability
  :
  Ensure Plant
  
  OS operates within safe bounds and degrades gracefully when things go wrong

Must Have

• 4‑7 years in product management, with experience in industrial software, or technical products
• Strong communication and stakeholder management skills—you can translate between operators, engineers, and ML teams
• Experience working on data‑intensive or ML‑powered products
• Demonstrated ability to ship products in complex technical environments
• Comfort with ambiguity and willingness to learn a deep technical domain
• Willingness to travel to plant sites to understand operations firsthand

Nice to Have

• Background in chemical engineering, metallurgy, process engineering, or chemistry
• Experience with process control, SCADA/DCS systems, or industrial automation
• Familiarity with reinforcement learning or ML‑based optimization
• Experience in mineral processing, refining,…