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Internship German Machine Learning Jobs in Inkster, MI

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 ...

We are seeking a German intern/trainee (Praktikant - w/m/d) for our US offices. The internship will ... We keep our employees current by supplying cutting-edge technology and access to learning ...

Full Year Intern-IT

Detroit, MI · On-site

$14.75 - $19.75/hr

Knowledge of deep learning, machine learning, and neural networks. * Working knowledge of Python, SQL, and Power BI. The Internship Program at BCBSM is designed to enhance the skills and abilities of ...

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Internship German Machine Learning information

See Inkster, MI salary details

$23.9K

$39.9K

$82.4K

How much do internship german machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for internship german machine learning in Inkster, MI is $39,854.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,400.00 and $43,100.00 per year, depending on experience, location, and employer.

Which 3 jobs will survive AI?

Jobs that require complex human skills such as machine learning engineers, data scientists, and cybersecurity specialists are likely to persist as AI automates routine tasks. These roles demand critical thinking, creativity, and specialized knowledge that are difficult for AI to replicate fully. Continuous learning and expertise in AI tools can enhance job security in these fields.

What is an Internship German Machine Learning?

An Internship German Machine Learning is a temporary training position typically offered by companies or research institutions in Germany, focusing on practical experience in machine learning. Interns work on real-world projects involving data analysis, algorithm development, and model implementation under supervision. These internships help students or recent graduates gain hands-on skills, industry exposure, and networking opportunities in the rapidly growing field of artificial intelligence and machine learning.

What is the difference between Internship German Machine Learning vs Data Scientist German?

AspectInternship German Machine LearningData Scientist German
Required CredentialsBasic programming, coursework in MLAdvanced degree in data science, statistics, or related
Work EnvironmentInternship setting, learning-focusedFull-time, project-driven
Industry UsageEntry-level roles, training programsProfessional roles, decision-making

Internship German Machine Learning positions are typically entry-level, focusing on learning and skill development, often requiring basic programming and coursework. Data Scientist German roles are more advanced, requiring higher education and experience, with responsibilities in analyzing data and building models. The internship provides a stepping stone into the data science field, while the data scientist role involves applying expertise to solve complex problems.

Can foreigners intern in Germany?

Foreigners can intern in Germany if they meet visa and work authorization requirements, which vary depending on their nationality and the internship duration. Internships often require a valid visa or residence permit, especially for non-EU/EEA citizens, and may need to comply with labor laws and internship regulations. It is important to check specific visa conditions and employer sponsorship options before applying.

How much do ML interns get paid?

Machine Learning interns typically earn between $15 and $30 per hour, depending on the company, location, and level of experience. Paid internships often include opportunities to work with tools like Python, TensorFlow, or PyTorch and may be full-time or part-time during the summer or semester.

What types of projects can I expect to work on during a German Machine Learning internship?

As a German Machine Learning intern, you'll typically assist with real-world projects such as developing and testing machine learning models, preprocessing datasets, and supporting the implementation of AI solutions in both German and international contexts. You may also help with data analysis, model evaluation, and documentation, often collaborating with data scientists and engineers. These projects provide hands-on experience with industry-standard tools and workflows, helping you build practical skills and a strong professional network.

What are the key skills and qualifications needed to thrive as an Internship German Machine Learning, and why are they important?

To thrive as an Internship German Machine Learning, you need a solid understanding of machine learning concepts, programming skills in Python, and progress toward a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, and data analysis libraries, as well as experience using version control systems like Git, is typically required. Strong analytical thinking, problem-solving ability, and effective communication—especially in both English and German—help you collaborate within diverse teams. These skills and qualifications are essential for successfully contributing to machine learning projects and adapting to the fast-evolving tech industry.

Is AI in demand?

AI skills are highly in demand for machine learning internships, including roles focused on developing and applying artificial intelligence technologies. Companies seek candidates with knowledge of programming languages like Python, experience with frameworks such as TensorFlow or PyTorch, and understanding of data analysis. The AI industry continues to grow, creating numerous opportunities for interns with relevant skills and training.
What cities near Inkster, MI are hiring for Internship German Machine Learning jobs? Cities near Inkster, MI with the most Internship German Machine Learning job openings:

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

$120K - $160K/yr

Full-time

Re-posted 3 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.