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Associate Full Stack Machine Learning Engineer Jobs in Saline, MI

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/yr

As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning ... We take full responsibility for outcomes, relentlessly driving toward solutions. Engineer Out ...

Stefanini

Machine Learning Engineer

Allen Park, MI · On-site

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI) For quick apply, please reach out to Navneet Pathak at / We are looking for a candidate who is responsible for predicting and/ or ...

Bespoke Labs

Machine Learning Engineer

Ann Arbor, MI

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Bespoke Labs

Machine Learning Engineer

Ann Arbor, MI · On-site

Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics * Implement methods from recent ML papers quickly and turn ...

Domino's Pizza

Lead Machine Learning Engineer

Ann Arbor, MI · On-site

$100K - $132K/yr

Serve as a senior technical resource for Machine Learning, AI, and Generative AI initiatives. * Provide technical leadership and mentorship to engineers and data scientists. * Translate business ...

Domino's

Lead Machine Learning Engineer

Ann Arbor, MI · On-site

$100K - $132K/yr

Serve as a senior technical resource for Machine Learning, AI, and Generative AI initiatives. * Provide technical leadership and mentorship to engineers and data scientists. * Translate business ...

Max AI, Inc.

Full-Stack Engineer

Ann Arbor, MI · On-site

$140K - $220K/yr

Full Stack Engineer Responsibilities * Taking ownership of the entire product lifecycle-from ... A dedication to continuous learning and personal development. * A positive, collaborative spirit ...

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All JobsAssociate Full Stack Machine Learning Engineer JobsAssociate Full Stack Machine Learning Engineer Jobs in Saline, MI

Associate Full Stack Machine Learning Engineer information

See Saline, MI salary details

$40.1K

$121.4K

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How much do associate full stack machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for associate full stack machine learning engineer in Saline, MI is $121,424.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $142,400.00 per year, depending on experience, location, and employer.
Associate Full Stack Machine Learning Engineer jobs near you
Infographic showing various Associate Full Stack Machine Learning Engineer job openings in Saline, MI as of September 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 80% In-person, and 20% Remote job distribution, with an average salary of $121,424 per year, or $58.4 per hour.

Machine Learning Engineer

Ann Arbor, MI • On-site

Mariana Minerals
See more jobs at Mariana Mineralsexternal

$120K - $180K/yr

Full-time

Re-posted yesterday

Key responsibilities

  • Run reinforcement learning experiments in physically realistic simulators of mineral processing operations and help improve control models.

  • Build and refine training environments, including reward functions, observations, and action logic, with guidance from senior engineers.

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

Job 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 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
  • 2-8+ 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.
Our culture is built on four principles:
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.
Join us as we build the future of responsible mineral sourcing and supply!

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