ZipRecruiter

Log In

1

Internship Machine Learning Hardware Jobs in Michigan

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 ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director ... Experience in deploying models to edge hardware, including experience with PyTorch and ONNX and ...

next page

Showing results 1-20

All JobsMachine Learning Hardware JobsInternship Machine Learning Hardware JobsInternship Machine Learning Hardware Jobs in Michigan

Internship Machine Learning Hardware information

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

AspectInternship Machine Learning HardwareInternship Data Scientist
Required CredentialsBasic knowledge of hardware, electronics, and programmingStatistics, programming, and data analysis skills
Work EnvironmentHardware labs, electronics workshops, manufacturing settingsOffice, data analysis environments, cloud platforms
Employer & Industry UsageTech companies, hardware manufacturers, research labsTech firms, finance, healthcare, consulting
Common Search & Comparison IntentUnderstanding hardware-focused roles in ML projectsData analysis and modeling roles in ML

Internship Machine Learning Hardware focuses on developing and optimizing hardware components for ML systems, while Internship Data Scientist emphasizes analyzing data and building models. Both roles are essential in AI development but differ in skills, environment, and industry application.

What is an Internship in Machine Learning Hardware?

An Internship in Machine Learning Hardware is a temporary position for students or recent graduates to gain hands-on experience working with the physical components and systems that enable machine learning applications. Interns typically assist in designing, testing, and optimizing hardware such as GPUs, TPUs, or custom accelerators that run machine learning algorithms efficiently. This role often involves collaboration with software engineers and researchers to improve the performance and energy efficiency of machine learning models. The internship provides valuable exposure to both hardware engineering and the rapidly evolving field of artificial intelligence.

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

To thrive as an Internship Machine Learning Hardware, you need a solid foundation in computer engineering, electrical engineering, or computer science, with coursework or experience in machine learning and hardware design. Familiarity with hardware description languages (like Verilog or VHDL), Python, C++, and tools such as TensorFlow, PyTorch, or FPGA development environments is typically required. Strong problem-solving abilities, eagerness to learn, and effective teamwork and communication skills help interns excel in multidisciplinary environments. These competencies are crucial for contributing to hardware-accelerated machine learning solutions and collaborating efficiently with engineering teams.

What kinds of projects and responsibilities can I expect during an Internship in Machine Learning Hardware?

As an intern in Machine Learning Hardware, you can expect to work on tasks such as benchmarking hardware performance for AI workloads, supporting the development and testing of new accelerator architectures, and optimizing hardware-software integration for machine learning models. You'll often collaborate with both hardware engineers and machine learning researchers, gaining exposure to the entire workflow from design to deployment. These internships typically provide hands-on experience with tools like FPGA, ASIC simulation environments, or specialized ML hardware platforms, and offer opportunities to contribute to real-world product development and research.
What are popular job titles related to Internship Machine Learning Hardware jobs in Michigan? For Internship Machine Learning Hardware jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Internship Machine Learning Hardware jobs in Michigan look for? The top searched job categories for Internship Machine Learning Hardware jobs in Michigan are:
What cities in Michigan are hiring for Internship Machine Learning Hardware jobs? Cities in Michigan with the most Internship Machine Learning Hardware job openings:
Internship Machine Learning Hardware jobs near you

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

$120K - $160K/yr

Full-time

Posted 28 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.

Apply