Machine Learning Engineer

Mariana Minerals is building machine learning systems that help control mineral refining facilities. This onsite role in Ann Arbor, MI focuses on reinforcement learning in physically realistic simulators, improving how models generalize to real plant data, and shipping trained models into production.

Compensation for this position is $120,000 - $180,000 per year. The role requires 2+ years of relevant experience (with consideration for internships and research), and the work spans end-to-end ownership from experimentation to deployment.

How you’ll create impact

• Run reinforcement learning experiments in physically realistic simulators of mineral processing operations, and translate experiment results into better controllers.
• Build and refine components of training environments, including reward functions, observations, and action logic, with guidance from senior engineers.
• Train control models, track and interpret performance, and investigate why a model underperforms.
• Close the gap between simulation and reality by comparing model behavior against real plant data and flagging where physics diverges.
• Write clean, well-tested code and contribute to services that move models into production.
• Work with process and chemistry experts to understand unit operations being modeled.

What you’ll work with

The tooling draws from reinforcement learning ecosystems used in self-driving vehicles and humanoid robots, 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.

Training happens inside physically realistic simulators of process units, followed by comparison against real plant data before models are introduced to live equipment.

What you bring

• 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, including comfort reading and debugging an existing codebase.
• Curiosity about physical, industrial systems, plus eagerness to learn chemistry and process engineering from experts who will challenge assumptions.
• A self-starter who asks good questions, ships, and escalates blockers early.

Culture and operating principles

• Extreme Ownership – take full responsibility for outcomes and relentlessly drive toward solutions.
• Engineer Out Requirements, then Automate – simplify, optimize, and automate for scale.
• Share Your Legos – collaborate openly, share knowledge, and empower each other to build bigger solutions.

Why this work matters

Mariana Minerals owns the projects, generates the data, and closes the loop between model development and real facility performance. Each facility improves the software, making the next facility faster and cheaper. This role supports modern software rebuilding in one of the last major industrial sectors that has not yet been extensively transformed, and your work directly contributes to scaling how critical minerals are produced.