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Machine Learning Internship No Experience Jobs in Michigan

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

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 ...

Rocket

Machine Learning Engineer

Detroit, MI · On-site

Required : • Master's degree in software development, computer science, algorithm design, artificial intelligence, or machine learning or equivalent experience Preferred : • 1 year of experience ...

Rock Connections

Machine Learning Engineer

Detroit, MI · On-site +1

$107K - $241K/yr

... can use to learn from experience, predict outcomes, and make decisions. About the role ... In no event will the Company reduce the compensation for the position to a level below the ...

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Machine Learning Internship No Experience information

What are the key skills and qualifications needed to thrive as a Machine Learning Intern with no prior experience, and why are they important?

To thrive as a Machine Learning Intern with no experience, you need a solid understanding of programming (especially Python), basic statistics, and foundational machine learning concepts, often demonstrated through coursework or personal projects. Familiarity with tools like scikit-learn, TensorFlow, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected. Curiosity, eagerness to learn, problem-solving ability, and effective communication are standout soft skills in this position. These skills and qualities are crucial for adapting quickly, contributing to projects, and maximizing growth in a hands-on learning environment.

What is a machine learning internship with no experience?

A machine learning internship with no experience is an entry-level opportunity designed for students or individuals who are new to the field of machine learning and may not have previous professional experience. These internships typically focus on foundational skills such as data preprocessing, understanding basic algorithms, and using popular tools like Python, TensorFlow, or PyTorch. Interns are often provided with mentorship, training, and real-world projects to help them learn and apply machine learning concepts. The goal is to gain practical experience and build a portfolio, which can be helpful for future job opportunities in the field.

What types of projects or tasks are typically assigned to machine learning interns with no prior experience?

Machine learning interns with no prior experience are often assigned to support tasks such as data preprocessing, exploratory data analysis, and helping to clean or organize datasets. They may also assist with implementing, testing, or tuning basic machine learning models under the guidance of experienced team members. Interns are encouraged to participate in team meetings, contribute to code reviews, and learn about the deployment process, giving them valuable exposure to real-world workflows and collaboration within a machine learning team.

What is the difference between Machine Learning Internship No Experience vs Data Science Intern No Experience?

AspectMachine Learning Internship No ExperienceData Science Intern No Experience
Required CredentialsBasic programming skills, introductory knowledge of ML conceptsBasic programming skills, introductory knowledge of data analysis
Work EnvironmentTech companies, startups, research labsTech companies, consulting firms, research organizations
Employer & Industry UsagePrimarily in AI and ML-focused rolesBroader data analysis and business intelligence roles
Search & Comparison IntentUnderstanding entry-level ML roles for beginnersExploring data analysis internships for beginners

Both internships are entry-level roles requiring foundational skills in programming. Machine Learning Internships focus on developing algorithms and models, while Data Science Internships emphasize data analysis and visualization. The choice depends on your interest in AI/ML versus broader data analysis tasks.

What are popular job titles related to Machine Learning Internship No Experience jobs in Michigan? For Machine Learning Internship No Experience jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Machine Learning Internship No Experience jobs in Michigan look for? The top searched job categories for Machine Learning Internship No Experience jobs in Michigan are:
What cities in Michigan are hiring for Machine Learning Internship No Experience jobs? Cities in Michigan with the most Machine Learning Internship No Experience job openings:
Machine Learning Internship No Experience jobs near you

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

$120K - $160K/yr

Full-time

Posted 24 days ago

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
  • 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.
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.

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