ZipRecruiter

Log In

1

Physics Informed Machine Learning Jobs (NOW HIRING)

ExxonMobil

Computational Scientist

Spring, TX · On-site

... physics-informed machine learning, reduced-order modeling, multi-fidelity methods, etc.) to reduce computational cost in decision-making processes (e.g., optimization, inverse problems, data ...

Digital Harbor Foundation

Research Scientist

Baltimore, MD · On-site +1

$120K - $150K/yr

Design and implement physics-informed machine learning models to improve predictive accuracy * Quickly learn and apply new tools, datasets, and methods to address evolving project needs * Apply ...

The Pennsylvania State University

The core objective of this research is to advance physics-informed machine learning architectures to process complex, real-world geodetic and acoustic datasets for subsurface energy applications. The ...

NEC Labs America

ML - Research Intern 2026

Princeton, NJ · On-site

$6.20K - $8.20K/mo

Ongoing projects focus on multimodal reasoning and planning, multimodal LLM, agentic generative AI, structured AI, workflow AI, AI safety, physics informed machine learning, and generative embodied ...

Causal Labs

Machine Learning - Research

San Francisco, CA

$241.50K/yr

Strong grasp of machine learning fundamentals, and depth in at least one core domain (e.g ... Computer Vision, Sensor Fusion, Language Models, Physics-informed NNs) * Experience training models ...

next page

Showing results 1-20

People also search for

All JobsPhysics Informed Machine Learning Jobs

Physics Informed Machine Learning information

See salary details

$5

$20

$25

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

As of Jun 2, 2026, the average hourly pay for physics informed machine learning in the United States is $20.06, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $25.48 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.
More about Physics Informed Machine Learning jobs
What cities are hiring for Physics Informed Machine Learning jobs? Cities with the most Physics Informed Machine Learning job openings:
What states have the most Physics Informed Machine Learning jobs? States with the most job openings for Physics Informed Machine Learning jobs include:
What job categories do people searching Physics Informed Machine Learning jobs look for? The top searched job categories for Physics Informed Machine Learning jobs are:
Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $41,731 per year, or $20.1 per hour.
Staff Machine Learning Engineer, Energy & Charging

Staff Machine Learning Engineer, Energy & Charging

Tesla

Palo Alto, CA • On-site

Full-time

Posted 20 days ago

Tesla rating

8.5

Company rating: 8.5 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

1st of 44 rated automakers

Job description

Job Summary:
Tesla is looking for an exceptional Machine Learning Engineer to build predictive life models to drive the future of intelligent Tesla products. The role involves collecting large datasets and developing machine learning models to enhance decision-making and design actions for Charging & Energy products.
Responsibilities:
• Design, develop, train, and deploy predictive / control models of physical degradation, usage and system performance
• Build robust, flexible and automated software tools to enable complex analysis of real-time fleet
• Design scalable and reliable data pipelines to productionize and monitor both new and existing models
• Convert complex business requirements and research findings into actionable insights and data-driven solutions
• Conduct research and remain up to date on the latest developments in AI/ML, with a special focus on physics-informed AI, to rapidly test and prototype new ideas
Qualifications:
Required:
• Proficiency in writing production-quality code in Python; experience with major deep learning frameworks, and software engineering best practices
• Practical experience with C to help integrate with firmware and take project ideas to shipped products
• Expertise in working with and optimizing large datasets, data pipelines, and AI models
• Solid understanding of linear algebra, probabilistic theory, numerical optimization, and deep learning, with hands-on implementation experience
• General knowledge of physics and engineering principles
Preferred:
• Record of coming up with new ideas (or improving upon existing ideas) in statistical modeling or machine learning, demonstrated by accomplishments such as first author publications or open-source projects
Company:
Tesla is an electric vehicle and clean energy company that provides electric cars, solar, and renewable energy solutions. Founded in 2003, the company is headquartered in Austin, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Tesla employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply