Mariana Minerals Logo

Mariana Minerals

Machine Learning Engineer

Posted 2 Days Ago
In-Office
San Francisco, CA, USA
120K-160K Annually
Junior
In-Office
San Francisco, CA, USA
120K-160K Annually
Junior
Develop and train reinforcement-learning control models in realistic simulators, refine training environments and reward logic, analyze and improve model performance, close the sim-to-real gap with plant data, write well-tested production code, and collaborate with process and chemistry experts to deploy autonomous controllers optimizing recovery, reagent use, energy, and uptime.
The summary above was generated by AI
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 the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.

 
The Role

Mariana Minerals is building the critical minerals supply chain from the ground up—and we're looking for Machine Learning Engineers to help make it autonomous.

We're not a software company selling tools to mining operators. We are a mining company that builds software. Mariana designs, builds, commissions, and operates our own mines and refineries. We develop proprietary chemical processes and run them at lab, pilot, and commercial scale. Today, we're producing battery-grade lithium salts from real oil and gas wastewater in our facilities. Our first commercial-scale lithium production facility, Lithium One, is targeting initial production in Q1 of 2027.

As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning systems that control our mineral refining facilities. You'll start with well-scoped problems inside our simulators and training pipelines—and ramp quickly toward owning models that run on real, operating plants. Your work won't live behind dashboards or proxy metrics; you'll see its impact in real recovery rates, energy consumption, reagent usage, and uptime.

 
The Tech

This is some of the most interesting applied AI work happening today.

Our internal platform uses the same reinforcement learning toolkits that power self-driving vehicles and humanoid robots—but applied to autonomous, short-interval control of mineral refining circuits. Models adjust operating set points and configurations in real time, optimizing across lithium recovery, reagent consumption, energy intensity, and equipment uptime simultaneously.

The environment is noisy and non-stationary: wastewater compositions shift, ore grades change, equipment ages. The system must continuously adapt. The end goal is fully autonomous refining operations. When you ship here, you can literally watch the physics change.

Under the hood, that means training control models inside physically realistic simulators of our process units, then closing the gap against real plant data before anything touches live equipment.

 
What You’ll Do
  • Run reinforcement learning experiments in our physically realistic simulators of mineral processing operations, and help turn the results into better controllers.

  • Build and refine pieces of our training environments—reward functions, observations, and action logic—with guidance from senior engineers.

  • Train control models, track and interpret their performance, and dig into why a model underperforms.

  • Help close the gap between simulation and reality by comparing model behavior against real plant data and flagging where the physics diverges.

  • Write clean, well-tested code and contribute to the services that put models into production.

  • Partner with process and chemistry experts to understand the unit operations you're modeling.

     
Desired Qualifications
  • 0–4 years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing—or a strong recent graduate with demonstrated project depth.

  • Solid grounding in machine learning fundamentals, with working knowledge of modern deep learning; exposure to reinforcement learning is a strong plus.

  • Proficiency in Python and comfort reading and debugging an existing codebase.

  • Curiosity about physical, industrial systems and eagerness to learn chemistry and process engineering from experts who will challenge your assumptions.

  • A self-starter who asks good questions, ships, and escalates blockers early.

     
Why This Role

We own the projects, generate the data, and close the loop. Every facility we build makes the software smarter—and the next facility faster and cheaper.

Mining is one of the last major industrial sectors that hasn't been rebuilt with modern software. The opportunity here isn't a feature gap—it's entire workflows and systems that don't exist yet.

Your work will directly shape how critical minerals are produced at scale in the coming decades.


Why Join Us?

At Mariana Minerals, you’ll be part of a mission-driven team reshaping the way critical minerals are sourced and supplied globally. You’ll have the autonomy to make big decisions, the tool


Our culture is built on three principles:

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.

Join us as we build the future of responsible mineral sourcing and supply.

 

Mariana is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.

Similar Jobs

Yesterday
Remote or Hybrid
Mountain View, CA, USA
Senior level
Senior level
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Build, ship, and operate end-to-end production AI/ML solutions for vehicle diagnostics, prognostics, and test analytics. Implement ML pipelines on Azure/Databricks, develop observable ML services, ensure model/data observability, and collaborate with SMEs to embed models into engineering workflows while mentoring other practitioners.
Top Skills: Ci/CdDatabricksExperiment TrackingAzureMlflowModel RegistriesPythonPyTorchScikit-LearnSparkSQLTensorFlow
7 Days Ago
Remote or Hybrid
2 Locations
185K-335K Annually
Senior level
185K-335K Annually
Senior level
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Lead design and development of scalable, high-performance ML training infrastructure. Drive distributed training performance optimization, observability, and developer experience. Own cross-functional infrastructure initiatives, set technical direction and standards, and mentor engineers to deliver platform capabilities that support large-scale model training.
Top Skills: AWSAzureDistributed TrainingFsdpGCPGpu ComputingPipeline ParallelismPythonPytorch 2.XTensorFlow
3 Days Ago
Remote or Hybrid
United States
153K-184K Annually
Senior level
153K-184K Annually
Senior level
Artificial Intelligence • Automotive • Robotics • Software • Transportation
Develop and deploy machine learning solutions for autonomous truck applications: EDA, deep learning model development, embedded deployment, data ingestion/curation, analytics, visualization, technical leadership, and process improvement across manufacturing and business domains.

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account