Home › Companies › Marianaminerals › Senior Machine Learning Engineer
Senior Machine Learning Engineer
Marianaminerals · San Francisco HQ · On Site · Deleted · Ashby
Job facts
| Field | Value |
|---|---|
| Company | Marianaminerals |
| Title | Senior Machine Learning Engineer |
| Normalized title | - |
| Department / team | Software Development / Software Development |
| Location | San Francisco, CA, United States |
| Work model | On Site |
| Employment type | Full Time |
| Salary | - |
| Status | deleted |
| ATS provider | Ashby |
| Posted / first seen | — / 2026-05-29 |
| Changed / last seen | 2026-06-12 / 2026-06-10 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Marianaminerals. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Ashby. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in San Francisco. | Open |
| Department jobs | Active postings in Software Development. | Open |
| Work model jobs | Active On Site postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Marianaminerals |
| Source | fa46a65b-a38d-43f6-a567-eac403fabac5 |
| ATS provider | Ashby |
Description
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 a Senior+ Machine Learning Engineer 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 the first half of 2027.
As a Senior Machine Learning Engineer at Mariana, you’ll lead the development and deployment of machine learning systems that directly control the operation of our mineral refining facilities and inform major investment and operational decisions. 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 on operating plants.
The Tech This is some of the most interesting applied AI work happening today.
Our internal platform, PlantOS , 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.
What You’ll Do Partner closely with Mariana’s process chemistry and engineering teams to develop novel, data-driven models of core chemical unit operations.
Train and deploy reinforcement learning models to control real-world mineral processing operations.
Use physically realistic simulators to pretrain RL control algorithms, and work with subject matter experts to diagnose gaps between simulated and real-world performance.
Build and maintain techno-economic models that integrate process simulation with capital costs, operating costs, and commodity price scenarios to inform investment and operational strategy.
Collaborate with internal teams on sensor and instrumentation strategy, incorporating inline measurement data to improve model performance.
Help design and evolve Mariana’s data architecture, including pipelines for training, validation, deployment, and monitoring of production ML systems.
Desired Qualifications 4+ years of post-school experience in machine learning engineering or a closely related role.
Strong grounding in machine learning fundamentals, with the ability to translate research ideas into novel production systems.
Experience with techno-economic modeling, process simulation, and/or quantitative analysis in complex systems.
Proven ability to develop, deploy, and operate ML models in production environments.
A self-starter mindset and comfort operating in high-ambiguity environments. You’ll work directly with chemical engineers, metallurgists, process engineers, and geologists—experts who understand the physics deeply and will challenge assumptions.
Ability to work across the ML stack, from data pipelines to model inference and monitoring, or deep expertise in one area with a desire to grow across the stack.
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 tools to innovate, and a culture that values ownership, smart automation, and collaboration.
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.
Full job record
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| Board ID | fa46a65b-a38d-43f6-a567-eac403fabac5 |
| Provider | ashby |
| Provider Job Key | 0eaee52a-89d7-492a-9c08-d7caa1813d00 |
| Title | Senior Machine Learning Engineer |
| Normalized Title | — |
| Status | deleted |
| Active | no |
| Location Text | San Francisco HQ |
| Department | Software Development |
| Team | Software Development |
| Employment Type | full_time |
| Workplace Type | on_site |
| Remote Policy | — |
| Country | United States |
| Region | CA |
| City | San Francisco |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://jobs.ashbyhq.com/marianaminerals/0eaee52a-89d7-492a-9c08-d7caa1813d00 |
| Apply URL | https://jobs.ashbyhq.com/marianaminerals/0eaee52a-89d7-492a-9c08-d7caa1813d00/application |
| First Seen At | 2026-05-29 07:11:24Z |
| Last Seen At | 2026-06-10 10:12:13Z |
| Last Checked At | 2026-06-12 09:45:23Z |
| Last Changed At | 2026-06-12 09:45:23Z |
| Inactive At | 2026-06-12 09:45:23Z |
| Source Posted At | — |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=ashby/board=marianaminerals/date=2026-06-10/2026-06-10T10-11-37-160Z-8446ebc97ac9ece9426f3b429117473e366cc4c8257fc1d884ee2028cb079b97.json |
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