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Internship Machine Learning R Jobs in Michigan (NOW HIRING)

... on academic, internship, personal, or professional projects. - Strong Python foundation and hands-on experience with at least one machine learning library or framework such as scikit-learn ...

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 ...

JOB SUMMARY We are looking for a Machine Learning engineer with Python, ML, Azure ML, A/B Testing ... Python, Databricks, Azure ML, Azure Cognitive Service, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit ...

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

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Internship Machine Learning R information

What is the difference between Internship Machine Learning R vs Data Analyst Intern?

AspectInternship Machine Learning RData Analyst Intern
Required SkillsProficiency in R, basic machine learning concepts, data preprocessingExcel, SQL, data visualization, basic statistical analysis
Work EnvironmentResearch labs, tech companies, startups focusing on AI/ML projectsBusiness environments, consulting firms, marketing agencies
Industry UsagePrimarily in tech, AI, and data science sectorsAcross various industries including finance, marketing, and healthcare

Internship Machine Learning R focuses on applying R programming to develop machine learning models, often in tech and AI sectors. In contrast, Data Analyst Internships emphasize data visualization, statistical analysis, and reporting across diverse industries. Both roles require data handling skills but differ in their focus on machine learning versus data interpretation.

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

Full-time

Posted 15 days ago


Job description

Job Summary:
Mariana Minerals is a software-first, vertically integrated minerals company focused on supplying critical minerals for modern energy and technology. They are seeking a Machine Learning Engineer to develop and improve machine learning systems for mineral refining facilities, working with real data to enhance operational efficiency.
Responsibilities:
• 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.
Qualifications:
Required:
• 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.
Company:
Mariana Minerals is a software-first critical minerals company that supplies materials essential for modern energy. Founded in 2022, the company is headquartered in Houston, USA, with a team of 51-200 employees. The company is currently Growth Stage.