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Scientific Machine Learning Jobs in Michigan (NOW HIRING)

The Machine Learning Engineer will be an essential member of the Research and Development Team ... Required Qualifications * BS. in Computer Science, or related field. * 3+ years of professional ...

Machine Learning Engineer

Dearborn, MI · Remote

$51.25 - $68.50/hr

Bachelor's degree in Computer Science, Information Systems, or a related field. * 3+ years of experience in developing and deploying machine learning models in a production environment. * 3+ years of ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Requires a minimum of 8 years of related experience with a Bachelor's degree in Computer Science ... Prior success in deploying impactful Machine Learning solutions to large-scale production systems ...

Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 ... Prior success in deploying impactful Machine Learning solutions to large-scale production systems ...

Machine Learning Engineer

Dearborn, MI

$105.50K - $126.60K/yr

Stefanini is looking for a Machine Learning Engineer (Dearborn, MI) For quick apply, please reach ... D. or foreign equivalent degree in Computer Science, Software Engineering, Information System, Data ...

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain ... You collaborate with engineers, data scientists, and product teams to define problems, test ...

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Scientific Machine Learning information

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Michigan? For Scientific Machine Learning jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Michigan look for? The top searched job categories for Scientific Machine Learning jobs in Michigan are:
What cities in Michigan are hiring for Scientific Machine Learning jobs? Cities in Michigan with the most Scientific Machine Learning job openings:

Machine Learning Engineering Intern

Mariana Minerals

Ann Arbor, MI • On-site

$25 - $35/hr

Internship

Posted 13 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
We are hiring a Machine Learning Engineering Intern to work on real, high-impact problems within our applied ML and operations team. You will contribute directly to building and improving models that influence real-world industrial systems and decision-making.
This role is designed to provide hands-on experience building and deploying machine learning solutions in production-like environments. You will work closely with engineers and domain experts to understand complex systems and apply ML techniques to improve performance, efficiency, and reliability.
What You'll Do
  • Work on a defined ML project with clear deliverables by the end of the internship
  • Build and experiment with models using Python, PyTorch/TensorFlow, or similar tools
  • Analyze real-world datasets to identify patterns, anomalies, and optimization opportunities
  • Support development of data pipelines, feature engineering, and model evaluation
  • Collaborate with engineers and domain experts to understand system behavior and constraints
  • Run experiments, validate results, and iterate based on findings
  • Document your work and present outcomes and learnings at the end of the internship

Qualification
  • Currently pursuing a degree in Computer Science, Machine Learning, Data Science, Chemical Engineering, or related field
  • Strong fundamentals in machine learning, statistics, and/or data analysis
  • Proficiency in Python and familiarity with ML frameworks (PyTorch, TensorFlow, etc.)
  • Hands-on experience through projects, coursework, or internships
  • Ability to break down problems and execute independently
  • Clear communication skills and willingness to learn in a fast-paced environment

Why Join Us?
At Mariana Minerals, you'll be part of a mission-driven team reshaping the way critical minerals are sourced and supplied globally. You'll have the autonomy to make big decisions, the tools to innovate, and a culture that values ownership, smart automation, and collaboration.
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.
Mariana is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.