ZipRecruiter

Log In

1

Physics Informed Machine Learning Jobs in Ann Arbor, MI

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning ... When you ship here, you can literally watch the physics change. Under the hood, that means training ...

A123 Systems LLC

Battery Modeling Engineer

Novi, MI · Hybrid

Develop physics-based models to identify aging mechanisms and optimize cell design. * Develop data-driven AI machine learning models to optimize the design of battery cell manufacturing process ...

A123 Systems Corp.

Battery Modeling Engineer

Novi, MI · On-site

Develop physics-based models to identify aging mechanisms and optimize cell design. * Develop data-driven AI machine learning models to optimize the design of battery cell manufacturing process ...

Pwc

AI Engineer

Detroit, MI

$50K - $112K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

New

Pwc

AI Engineer / Data Scientist, AI Manager

Detroit, MI · On-site

$99K - $297K/yr

Responsibilities - Leading the development and implementation of advanced AI and machine learning ... informed decision-making and drive business growth - Supervising and coaching teams to deliver ...

next page

Showing results 1-20

All JobsPhysics Informed Machine Learning JobsPhysics Informed Machine Learning Jobs in Ann Arbor, MI

Physics Informed Machine Learning information

See Ann Arbor, MI salary details

$5

$19

$24

How much do physics informed machine learning jobs pay per hour?

As of Jul 29, 2026, the average hourly pay for physics informed machine learning in Ann Arbor, MI is $19.63, according to ZipRecruiter salary data. Most workers in this role earn between $12.21 and $24.95 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are popular job titles related to Physics Informed Machine Learning jobs in Ann Arbor, MI? For Physics Informed Machine Learning jobs in Ann Arbor, MI, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Ann Arbor, MI look for? The top searched job categories for Physics Informed Machine Learning jobs in Ann Arbor, MI are:
What cities near Ann Arbor, MI are hiring for Physics Informed Machine Learning jobs? Cities near Ann Arbor, MI with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Ann Arbor, MI as of June 2026, with employment types broken down into 1% Internship, 73% Full Time, 18% Part Time, 2% Temporary, 5% Contract, and 1% Nights. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $40,827 per year, or $19.6 per hour.

Machine Learning Engineer

Mariana Minerals

Ann Arbor, MI • On-site

Full-time

Re-posted 18 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 critical minerals company that supplies materials essential for modern energy. Founded in 2022, the company is headquartered in Houston, USA, with a team of 51-200 employees. The company is currently Growth Stage.

Apply