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Internship Spacex Machine Learning Jobs in Michigan

Corning

... 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 ...

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 ...

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Internship Spacex Machine Learning information

What is the difference between Internship Spacex Machine Learning vs Data Science Intern?

AspectInternship Spacex Machine LearningData Science Intern
Required CredentialsRelevant coursework, basic programming skills, possibly some experience in MLStatistics, programming, data analysis skills, often a related degree
Work EnvironmentHands-on projects in aerospace, collaborative teams, fast-pacedData analysis, modeling tasks, diverse industries, team-based
Employer & Industry UsageSpaceX, aerospace, technology innovationVarious industries including tech, finance, healthcare

Internship Spacex Machine Learning focuses on applying ML techniques to aerospace challenges at SpaceX, emphasizing engineering and technical skills. Data Science Internships are broader, covering data analysis and modeling across multiple industries. Both roles require programming and analytical skills but differ in industry focus and project scope.

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Internship Spacex Machine Learning jobs near you

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

Full-time

Posted 3 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, vertically integrated minerals company focused on supplying the minerals critical to modern energy, AI, and defense technologies. Founded in , the company is headquartered in San Francisco, CA, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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