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Physics Informed Machine Learning Jobs in Philadelphia, PA

T-Mobile

Senior Data Science Engineer

Philadelphia, PA · On-site

$116K - $210K/yr

... physics, engineering, etc.) (Required) * 4-7 years experience building and deploying machine learning and deep learning solutions at scale; familiarity with MLOps and DevOps practices and tools ...

United States Cold Storage

Data Scientist II

Camden, NJ

$100K - $120K/yr

You will solve problems using statistical methods, machine learning, and AI. You will help the ... Master's degree in mathematics, statistics, physics, computer science or related field Helpful ...

USCS

Data Scientist II

Camden, NJ · On-site

$100K - $120K/yr

You will solve problems using statistical methods, machine learning, and AI. You will help the ... Master's degree in mathematics, statistics, physics, computer science or related field Helpful ...

United States Cold Storage

Data Scientist II

Camden, NJ · On-site

$100K - $120K/yr

You will solve problems using statistical methods, machine learning, and AI. You will help the ... Master's degree in mathematics, statistics, physics, computer science or related field Helpful ...

United States Cold Storage

Data Scientist II

Camden, NJ · On-site

$100K - $120K/yr

You will solve problems using statistical methods, machine learning, and AI. You will help the ... Master's degree in mathematics, statistics, physics, computer science or related field Helpful ...

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

As of Jun 10, 2026, the average hourly pay for physics informed machine learning in Philadelphia, PA is $20.25, according to ZipRecruiter salary data. Most workers in this role earn between $12.60 and $25.72 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 Philadelphia, PA? For Physics Informed Machine Learning jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Philadelphia, PA look for? The top searched job categories for Physics Informed Machine Learning jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Physics Informed Machine Learning jobs? Cities near Philadelphia, PA with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Associate Vice President of AI Product Engineering

Associate Vice President of AI Product Engineering

Penn Medicine

Philadelphia, PA

Other

Posted 8 days ago

Penn Medicine rating

7.6

Company rating: 7.6 out of 10

Based on 340 frontline employees who took The Breakroom Quiz

187th of 870 rated healthcare providers

Job description

Description
Penn Medicine is dedicated to our tripartite mission of providing the highest level of care to patients, conducting innovative research, and educating future leaders in the field of medicine. Working for this leading academic medical center means collaboration with top clinical, technical and business professionals across all disciplines.
Today at Penn Medicine, someone will make a breakthrough. Someone will heal a heart, deliver hopeful news, and give comfort and reassurance. Our employees shape our future each day. Are you living your life's work?
Entity: Corporate Services
Department: PennDNA
Location: 3600 Civic Center Blvd
Summary:
The Associate Vice President (AVP) of AI will be responsible for the development and deployment of machine learning solutions to address critical challenges for our health system. The AVP of AI oversees a team of data scientists and AI engineers. They will also take ownership of hands-on machine learning code development and/or deployment, when necessary, to ensure successful development and implementation.
Responsibilities:
  • Strategic Leadership: Develop and execute a strategic roadmap for machine learning initiatives that align with the health system's goals. Lead the creation of innovative AI/ML solutions to improve patient care, operational efficiency, and clinical outcomes. Communicate vision, gain buy-in, and foster collaboration with clinicians, operational leaders, and technology teams. Develop internal and external partnerships to foster collaboration and execution.
  • Technical Design and Oversight: Lead the technical design of machine learning solutions tailored to meet business, clinical, and operational requirements. Ensure the robustness, scalability, and performance of ML models in production environments. Establish best practices for code development, version control, testing, and deployment of ML solutions. Implement CI/CD pipelines for ML deployment. Collaborate with security, infrastructure, and application teams to ensure seamless integration of ML solutions into workflows.
  • Research & Development: Develop a pipeline of ML capabilities to explore, test, and develop with a view to production deployment and health system priorities. Stay informed about the latest advancements in machine learning and healthcare technology to guide continuous improvement and innovation. Communicate internally and externally, including publications, conference presentations, etc., as appropriate to advance our agenda.
  • Trustworthy AI: Develop and execute on a roadmap to trustworthy AI, including MLOps, model monitoring and retraining, explainability, application standards for security and privacy. Ensure compliance with relevant and evolving regulations (e.g. HIPAA, coming FDA regulations).
  • Team Management: Lead, mentor, and grow a team of data scientists, machine learning engineers, and software developers. Set high performance expectations and help team to achieve them. Create a positive culture that encourages collaboration and fosters innovation. Attract and retain top talent. Develop new leaders. Help others to find purpose amid uncertainty.
  • Stakeholder Engagement: Develop credibility and trust with leaders by demonstrating expertise, aligning around shared goals, and acting as a thought partner. Develop a deep understanding of customer needs and apply that knowledge to prioritize projects, design solutions, and execute. Influence a wide-range of senior leaders inside and outside PennDnA. Articulate vision, build consensus, and inspire action to achieve outcomes.
  • Continuous Improvement: Drive innovation and excellence across the organization, continuously seeking ways to enhance the use of data for informed decision-making. Stay abreast of industry trends, emerging technologies, and best practices in healthcare data analytics.

Education or Equivalent Experience:
  • Bachelor's Degree is required. Education Specialization: e.g., Computer Science, Mathematics, Data Science, Machine Learning.
  • 10+ years progressively responsible experience developing ML solutions, putting them into production, and scaling is required.
  • Master's Degree is required. Education Specialization: e.g., Computer Science, Mathematics, Data Science, Machine Learning.
  • Ph.D. is preferred.

#LI-ST1
We believe that the best care for our patients starts with the best care for our employees. Our employee benefits programs help our employees get healthy and stay healthy. We offer a comprehensive compensation and benefits program that includes one of the finest prepaid tuition assistance programs in the region. Penn Medicine employees are actively engaged and committed to our mission. Together we will continue to make medical advances that help people live longer, healthier lives.
Live Your Life's Work
We are an Equal Opportunity employer. Candidates are considered for employment without regard to race, ethnicity, color, sex, sexual orientation, gender identity, religion, national origin, ancestry, age, disability, marital status, familial status, genetic information, domestic or sexual violence victim status, citizenship status, military status, status as a protected veteran or any other status protected by applicable law.

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