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Physics Informed Machine Learning Jobs in Marlton, NJ

Pwc

CTIO AI Engineering Manager

Philadelphia, PA

$73K - $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 Aug 20, 2026, the average hourly pay for physics informed machine learning in Marlton, NJ is $20.42, according to ZipRecruiter salary data. Most workers in this role earn between $12.74 and $25.91 per hour, depending on experience, location, and employer.

What is a physics informed machine learning?

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 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 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.

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What cities near Marlton, NJ are hiring for Physics Informed Machine Learning jobs?

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Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Marlton, NJ as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $42,466 per year, or $20.4 per hour.

Electrical Engineering & Computer Science Patent Agent - Philadelphia

Direct Counsel

Philadelphia, PA • On-site, Remote

$140K - $250K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 days ago

Job description

Direct Counsel is partnered with an AmLaw 100 firm seeking mid-level patent agents to join their Electrical Engineering and Computer Science Patent Prosecution Practice Group. This position is open to all offices with emphasis on Atlanta, Denver, San Francisco, Seattle, St. Louis, Washington, DC, Houston, Kansas City, or Phoenix offices. Interested candidates must possess a high level of academic achievement, solid law firm, engineering, or industry experience, and superb writing and communication skills.

Responsibilities:

  • Prepare and prosecute patent applications in electrical engineering and software-related technologies

  • Conduct patentability searches and analysis

  • Draft responses to USPTO office actions

  • Collaborate with attorneys and clients to develop patent strategies

  • Review and analyze technical disclosures

Qualifications:

  • 2+ years of relevant patent preparation and prosecution experience

  • Degree in Electrical Engineering, Computer Engineering, Software Engineering, Computer Science, or Physics

  • Admission to the USPTO required

  • Excellent writing, communication, and analytical skills

  • Experience in data science, AI, networking technologies (including network security), machine learning, and hardware security is highly preferred

Compensation:

  • Salary range: $140,000 - $250,000 depending on experience

  • Discretionary performance-based bonus may be available

  • Eligible for firm benefits including: medical insurance, dental insurance, life insurance, disability insurance, voluntary vision insurance, 401(k) plan, and paid time off

Application Requirements:
Please submit a cover letter, resume, undergraduate transcript (and graduate when applicable), and writing sample (preferred patent application).