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Physics Informed Machine Learning Jobs in Milwaukee, WI

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$102.70K - $141K/yr

... Physics, etc.) or equivalent experience • 4+ years of experience working in data engineering, data science, software engineering, MLOps specializing in AI and Machine Learning deployment • 4+ ...

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Generac

Data Scientist II

Waukesha, WI

Bachelor's Degree in Computer Science, Math, Physics, Engineering, Statistics or related field, * 2+ years of experience post-grad in a Data Science / Machine Learning position. * Professional ...

Pwc

CTIO AI Engineering Manager

Milwaukee, WI

$73.50K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Generac

Engineer II - Engine Coding

Waukesha, WI

Apply data analysis techniques, including Matlab/Simulink modeling and Python-based scripting and machine learning, to support code performance forecasting. * Stay informed on relevant technologies ...

Generac

Senior Engine Code Engineer

Waukesha, WI

$104.60K - $143.60K/yr

Apply data analysis techniques, including Matlab/Simulink modeling and Python-based scripting and machine learning, to support code performance forecasting. * Stay informed on relevant technologies ...

Pwc

CTIO-AI Engineer-Sr Associate

Milwaukee, WI

$55K - $187K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Pwc

NGA AI Engineer Manager

Milwaukee, WI

$73.50K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

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

As of May 29, 2026, the average hourly pay for physics informed machine learning in Milwaukee, WI is $19.77, according to ZipRecruiter salary data. Most workers in this role earn between $12.31 and $25.10 per hour, depending on experience, location, and employer.

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 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.
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Physics Informed Machine Learning jobs near you

Applied Machine Learning Engineer II - Advanced Engineering & Technology

Milwaukee Tool

Brookfield, WI • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 21 days ago

Job description

Job Description:
Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time.
INNOVATE WITHOUT BOUNDARIES! At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success - so we give you unlimited access to everything you need to create disruptive new technologies and solutions.
Your Role on the Team:
As a member of the Advanced Engineering and Technology (AET) Team in the Power Tool Accessories business unit you will utilize your expertise in machine learning to solve problems where no established solution exists and deliver first-of-its-kind technologies at Milwaukee Tool. You will research, prototype, and deliver ML-driven capabilities that accelerate how we design and develop products. You will take ideas from conceptual whiteboard architectures through functional prototypes and hand-off integrations, delivering technology innovation to product and production engineering teams. This role is an individual contributor position focused on applied execution and technology demonstration, working under shared technical direction.
Why This Role is Different:
  • Full-Stack ML in a Physical Domain: Work across the ML stack, from machine and sensor-level data through model deployment on edge hardware or cloud infrastructure.
  • R&D Engineering First: Apply ML across Technology Readiness Levels (TRL 1-7), bringing technology innovation to life beyond model tuning. Domain knowledge in materials, mechanics, signals, or physics is central to this role.
  • Flexible Tools: Select and use frameworks and libraries best suited to the problem, without being constrained to a single ecosystem.
  • Real Impact: Deliver ML-driven capabilities that shorten product development cycles and unlock new engineering possibilities at Milwaukee Tool.

What You'll Do:
  • Research and evaluate emerging AI and ML technologies, advancing them through the Technology Readiness Level (TRL) process from concept through technology integration.
  • Frame engineering problems as ML problems by assessing ML value versus physics-based or analytical approaches and defining practical success criteria.
  • Design, train, evaluate, and deploy ML models to solve applied science and engineering problems that expand product development capabilities.
  • Build end-to-end ML workflows spanning data acquisition, feature engineering, model development, validation, and deployment (PyTorch, TensorFlow, CUDA, Azure ML).
  • Deploy ML enabled systems on edge hardware and cloud infrastructure to support engineering decisions.
  • Prepare technology transfer packages by documenting architecture decisions, known limitations, data requirements, and deployment specifications to enable technology adoption.
  • Collaborate with cross-functional teams to deliver ML solutions aligned with engineering needs.
  • Identify and assess emerging technologies via literature, universities, conferences, and vendor engagement.

What You'll Bring:
Required
  • BS in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, Computer Science, Data Science, or related engineering discipline, with advanced coursework or experience in Machine Learning.
  • +3 or more years of experience applying ML to physical-world engineering or scientific problems (materials, mechanical systems, manufacturing, sensor systems, chemical processes, or similar).
  • Demonstrated experience designing, training, evaluating, and deploying ML models on real-world problems.
  • Strong working knowledge of Python and the scientific computing ecosystem (NumPy, SciPy, Pandas, scikit-learn), with working knowledge of SQL.
  • Hands-on experience with at least one deep learning framework (PyTorch or TensorFlow) and familiarity with cloud ML platforms (Azure ML, AWS SageMaker, or equivalent).
  • Strong mathematical foundations in linear algebra, probability, statistics, and optimization, with the ability to reason about loss functions, convergence behavior, and model assumptions.
  • Demonstrated ability to formulate ambiguous engineering or scientific problems into well-defined ML problems with clear objectives and evaluation criteria.
  • Curiosity-driven approach to learning new technologies and methods, with emphasis on applying machine learning to real-world scientific and engineering challenges.
  • Ability to work across a diverse range of data types.
  • Hands-on approach to collaboration and evaluation of technologies.
  • Ability to thrive in an ambiguous and fast-paced environment, where problem definitions evolve.
  • Ability to travel 10% of the time (domestic and international).

Preferred
  • Master's Degree or PhD in relevant field.
  • Familiarity with physics-informed ML approaches, embedding physical constraints in model architecture, or surrogate modeling for simulation acceleration.
  • Experience with computer vision for engineering applications.
  • Exposure to edge deployment: model optimization containerized deployment to industrial hardware.
  • Experience with design of experiments (DOE), uncertainty quantification, or Bayesian optimization.
  • Familiarity with version control, experiment tracking, and reproducible research practices

Working Environment
  • In-Person, Office Environment, R&D Engineering Lab

Our Perks and Benefits:
  • Robust health, dental and vision insurance plans
  • Generous 401 (K) savings plan
  • Education assistance
  • On-site wellness, fitness center, food, and coffee service
  • And many more, check out our benefits site HERE.

Milwaukee Tool is an equal opportunity employer.

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