1

Physics Informed Machine Learning Jobs in Philadelphia, PA

Sets performance standards, reviews performance, and makes informed compensation decisions in ... Experience utilizing statistical and machine learning methods required. * Advanced Python ...

Sets performance standards, reviews performance, and makes informed compensation decisions in ... Experience utilizing statistical and machine learning methods required. * Advanced Python ...

next page

Showing results 1-20

Physics Informed Machine Learning information

See Philadelphia, PA salary details

$5

$20

$25

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

As of Jun 14, 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 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:

Senior Software Engineer - Modeling and Simulation

Integer Technologies

Philadelphia, PA

$123K - $163K/yr

Other

Posted 8 days ago


Job description

Senior Software Engineer – Modeling and Simulation

Integer Technologies is seeking a Senior Software Engineer reporting to the Digital Twin and Controls Engineering Manager within the Digital Engineering Division. This role will implement the research and development of novel approaches for representing machinery system performance as part of a larger effort to improve the performance and cybersecurity of machinery controls for defense applications.

Integer's products use digital engineering tools to support decision-making and optimization of large and complex integrated defense machinery systems. The Digital Twin and Controls team is focused on building digital twin-based controls platforms for advanced machinery applications. The goals of these controls platforms are optimizing system performance, improving system resilience, and reducing the cognitive burden of the users.

This role will extend the development of the models and simulation frameworks to support the improvement of the performance and cyber-physical resilience of advanced digital twin controls systems and will require a balance of software engineering, cybersecurity, and multi-physics modeling and simulation of machinery systems.

Objectives of this role:

  • Analyze technical needs for digital twin control systems, elicit actionable system requirements and develop robust software focusing on emulating physical systems and simulating notional machinery.
  • Create scalable software platforms and applications, as well as efficient networking solutions, that are unit tested, code reviewed, and checked regularly for continuous integration.
  • Identify and resolve issues in hardware and software systems, collaborating with cross-functional teams as needed.

Responsibilities:

  • Develop multi-physics computer models that accurately represent real-world systems
  • Apply physics-based and data-driven modeling techniques
  • Integrate models into full digital twin workflows for analysis and prediction
  • Architect scalable software frameworks that support digital twin functions
  • Collaborate using version control workflows with Git across multidisciplinary teams
  • Ensure smooth integration with live data streams from physical assets, sensors, or emulated equipment
  • Integrate models with analysis workflows to support real-time and faster-than-real-time decision making
  • Optimize trade-offs between simulation speed, accuracy, and system resource constraints
  • Conduct research on cutting-edge engineering topics where no current solutions exist
  • Document findings in a clear, accessible format for both technical and non-technical audiences
  • Work with teams of engineers and subject-matter experts on complex systems
  • Demonstrate a growth mindset, continuously expanding technical and domain-specific skills
  • Remain current with advancements in digital twin technologies and modeling tools
  • Exhibit organization and detail orientation while managing complex tasks

Required Qualifications:

  • Must be a U.S. Citizen with the ability to obtain and maintain a U.S. DoD Secret Clearance
  • Bachelor's degree in software engineering, electrical engineering, mechanical engineering, computer science, or a related technical discipline
  • 5+ years of professional software engineering experience-ideally building control systems, digital twins, or embedded applications
  • Proficiency working with computer modeling and simulation environments (e.g., MATLAB/Simulink, Modelica, or similar) in one of the following domains:
    • Electrical Power and Energy Systems
    • Thermal-Fluid and Cooling Systems
    • Machinery and Electromechanical Control Systems
  • Proficiency in a high-level programming language such as Python, C/C++, Java or others, with experience using scientific computing and numerical libraries.
  • Experience with software engineering principles, including object-oriented design, data management, multi-threading/multi-processing, and collaborative source control using Git.
  • Experience with debugging and optimizing solver performance, including convergence and stability issues
  • Experience writing software to interface with and process data streams from physical hardware, sensors, or network sources.
  • Excellent problem-solving skills and attention to detail.
  • Excellent communication and teamwork skills to collaborate effectively across departments.

Desired Qualifications:

  • Masters or PhD in a relevant engineering or computer science discipline.
  • Proficiency developing software solutions for defense applications.
  • Proficiency in software engineering principles, including object-oriented design, data management, multi-threading/multi-processing, and collaborative source control using Git.
  • Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) or numerical optimization methods.
  • Experience with database design and management (e.g., SQL, NoSQL).
  • Experience designing software solutions utilizing multiple network communication protocols (e.g., TCP/IP, SSL, TLS, DDS, REST) or hardware interface standards (e.g., CAN bus, Modbus).
  • Experience with parallel computing for high-performance simulations
  • Experience with real-time simulation platforms (e.g., OpalRT, Typhoon HIL, Speedgoat).
  • Experience with software testing methodologies, including unit testing, integration testing, and continuous integration (CI/CD).
  • Experience with simulation solver technologies and numerical integration methods.
  • Experience with front-end development for data visualization.

Screening questions:

  • Are you able to gain and obtain a Government Security Clearance; which consists of being a US Citizen?
  • Are you currently located or are you willing to explore relocation to Columbia, SC, and be in office on a Hybrid schedule (3 days a week)?
  • How many years of experience do you have in software development?
  • How many years of experience do you have in modeling and simulations development (e.g., physics-based simulations)