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Physics Informed Neural Networks Jobs in Washington, DC

Quid, Inc.

Senior Offline Mapping Engineer

Columbia, MD · On-site

$175 - $230/hr

Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs ... Expertise in neural scene representations (NeRF, Gaussian Splatting, or similar). * Experience with ...

Quidient

Senior Computer Vision Engineer

Columbia, MD · On-site

$160K - $210K/yr

Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs ... Experience with 3D reconstruction pipelines, including SfM, MVS, or neural scene representations ...

SOSi

Machine Learning Engineer- Senior

Chantilly, VA · On-site

$125K - $165K/yr

... informed decision-making. Qualifications Minimum Requirements * Existing TS/SCI (with poly). This ... neural networks. * Deploying models into multi-node Ray clusters utilizing various GPU resources.

SOSi

Machine Learning Engineer- Senior

Chantilly, VA

$125K - $165K/yr

... informed decision-making. Qualifications Minimum Requirements * Existing TS/SCI (with poly). This ... neural networks. * Deploying models into multi-node Ray clusters utilizing various GPU resources.

Quidient

Senior Offline Mapping Engineer

Columbia, MD · On-site

$175K - $230K/yr

Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs ... Expertise in neural scene representations (NeRF, Gaussian Splatting, or similar). * Experience with ...

Quid, Inc.

Senior Offline Mapping Engineer

Washington, DC · On-site

$175 - $230/hr

Words relevant to Quidient include Generative AI, Physics-Informed AI, Large Scene Models (LSMs ... Expertise in neural scene representations (NeRF, Gaussian Splatting, or similar). * Experience with ...

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Physics Informed Neural Networks information

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How much do physics informed neural networks jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for physics informed neural networks in Washington, DC is $22.72, according to ZipRecruiter salary data. Most workers in this role earn between $14.13 and $28.85 per hour, depending on experience, location, and employer.

What is a physics informed neural network?

A Physics Informed Neural Networks (PINNs) job typically involves developing and applying neural networks that incorporate physical laws as constraints to solve complex scientific and engineering problems. Professionals in this field work on integrating differential equations into deep learning models to improve predictions and reduce the need for large training datasets. These roles are common in fields like fluid dynamics, material science, and climate modeling, where traditional computational methods can be expensive. Individuals in this role often have expertise in machine learning, numerical methods, and domain-specific physics.

What does a physics informed neural network do?

In a Physics Informed Neural Networks role, your daily tasks will often include designing, building, and testing neural network architectures that incorporate physical laws and constraints. You will frequently collaborate with domain experts, such as physicists or engineers, to integrate scientific knowledge into machine learning models and validate the results with real-world data. Regular responsibilities also involve coding, running experiments, analyzing results, and documenting findings for presentation or publication. This collaborative and research-driven environment helps ensure that models are both accurate and physically consistent, and offers opportunities for interdisciplinary learning and skill advancement.

What are the key skills and qualifications needed to thrive in physics informed neural networks?

To thrive in Physics Informed Neural Networks (PINNs), you need a strong background in physics, mathematics, and deep learning frameworks, typically evidenced by advanced degrees in physics, applied mathematics, computer science, or engineering. Experience with programming languages such as Python, and familiarity with libraries like TensorFlow or PyTorch, as well as experience in numerical simulation tools, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help professionals excel in multidisciplinary teams. These qualifications and soft skills are essential for developing accurate, interpretable models that integrate scientific knowledge with machine learning to solve complex real-world problems.

What job categories do people searching Physics Informed Neural Networks jobs in Washington, DC look for?

The top searched job categories for Physics Informed Neural Networks jobs in Washington, DC are:

Physics Informed Neural Networks jobs near you
Infographic showing various Physics Informed Neural Networks job openings in Washington, DC as of August 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Hybrid job distribution, with an average salary of $47,264 per year, or $22.7 per hour.

Senior Engineer, Production

Venture Global, Inc.

Arlington, VA • On-site

$158K - $186K/yr

Full-time

Posted 11 days ago

Job description

Venture Global LNG ("Venture Global") is a long-term, low-cost provider of American-produced liquefied natural gas. The company's Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global's modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost.
We are seeking qualified applicants for the position:
Senior Engineer, Production
Located:
Arlington
Summary
We are seeking a Senior Production Engineer to join our team in our Arlington, VA office.
The Senior Production Engineer will report to the Principal Production Engineer and will be supporting Production engineering, Process engineering and Operations across all our facilities.
This role will be part of the Production engineering team responsible for ensuring the plant operations remain program compliant and that the production volumes are delivered in a safe and reliable manner. This is a fast-paced environment requiring drive, enthusiasm, willingness to learn and grow rapidly.
This position focuses on process modeling and simulation to understand plant performance, optimize production, and support day-to-day application of plant models. The successful candidate will work alongside experienced engineers and cross functional teams contributing to real-time operational decisions and support long-term/high impact decision making.
General Description Duties & Responsibilities
Candidate will develop a deep understanding of the Venture Global LNG process and responsibilities include, but not limited to:
  • Creating/validating steady-state and dynamic process models of the LNG process units using industry standard tools (e.g., Aspen HYSYS)
  • Using appropriate methodologies such data driven, physics-based and data analytics models depending on the objectives
  • Formulates solutions to create technology systems to sustain model recommendations to improve performance. This includes automation of models - engineering, AI and hybrid - as part of real-time systems
  • Engaging with stakeholders (engineering, IT, operations) and building positive relationships
  • Analyze plant data and model outputs to identify optimization opportunities and troubleshoot operational issues
  • Assist in evaluating the impact of process changes, debottlenecking studies and efficiency improvements
  • Innovating and driving continuous improvement
  • Travel to all our Louisiana LNG Facilities as needed

Qualifications
  • Bachelor's degree in Chemical Engineering. Higher degrees (Masters or PhD) preferred.
  • 5-10 years of relevant industry experience. LNG experience is a plus.
  • Must possess deep interest in physics-based engineering modeling, data analytics and data science/machine learning methodologies
  • Understands where each of the above approaches fit, i.e. strengths and weaknesses and applicability
  • Deep expertise in automation of engineering and AI models in a real-time environment
  • Engages with stakeholders across the organization to onboard and incorporate feedback
  • Familiarity with Microsoft Office 365 Application Suite, process modeling tools such as Unisim/Aspen HYSYS, AI models (e.g. neural networks)
  • Some basic programming skills is a plus (C++, Python etc.)
  • High level of energy and motivation to excel within the organization
  • Goes above and beyond and takes initiative

Salary Range
$158,000 - $186,000
Venture Global LNG is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by appropriate law.

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