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Internship Infosys Machine Learning Jobs in Michigan

... 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 ...

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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 Infosys Machine Learning information

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

AspectInternship Infosys Machine LearningData Science Intern
Required CredentialsBasic programming, understanding of ML algorithms, coursework in AI/MLStatistics, programming, data analysis coursework
Work EnvironmentCorporate setting, collaborative teams, project-basedResearch or corporate projects, data analysis tasks
Industry UsageTechnology, consulting, financeTech, finance, healthcare, research
Common Search IntentInternship opportunities, skills required, company-specific infoData analysis skills, project examples, career path

Internship Infosys Machine Learning focuses on applying machine learning algorithms in a corporate environment, often emphasizing programming and model deployment. Data Science Internships cover broader data analysis, statistics, and insights generation. Both roles require foundational technical skills, but Machine Learning internships are more specialized in AI/ML techniques, while Data Science internships encompass a wider range of data handling and analysis tasks.

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

Full-time

Re-posted yesterday


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.