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Physics Informed Machine Learning Jobs in Washington, DC

SOSi

Machine Learning Engineer- Senior

Chantilly, VA

$125K - $165K/yr

Overview SOSi is seeking a skilled Machine Learning Engineer to support a US government customer in ... informed decision-making. Qualifications Minimum Requirements * Existing TS/SCI (with poly). This ...

SOSi

Machine Learning Engineer- Senior

Chantilly, VA · On-site

$125K - $165K/yr

Overview SOSi is seeking a skilled Machine Learning Engineer to support a US government customer in ... informed decision-making. Qualifications Minimum Requirements * Existing TS/SCI (with poly). This ...

SOSi

Machine Learning Engineer- Senior

Chantilly, VA · On-site

$125K - $165K/yr

Overview SOSi is seeking a skilled Machine Learning Engineer to support a US government customer in ... informed decision-making. Qualifications Minimum Requirements * Existing TS/SCI (with poly). This ...

Navstar

Staff AI/ML Machine Learning Engineer

Herndon, VA · On-site +1

$132K - $234K/yr

AI/ML Machine Learning Engineer Herndon, VA Top Secret/SCI Polygraph Unspecified Career Level not ... Electrical Engineering, Computer Science, Computer Engineering, Mathematics, Physics) or equivalent ...

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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 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 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 Washington, DC? For Physics Informed Machine Learning jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Washington, DC look for? The top searched job categories for Physics Informed Machine Learning jobs in Washington, DC are:
Physics Informed Machine Learning jobs near you
Machine Learning Modeling and Simulation Engineer

Machine Learning Modeling and Simulation Engineer

Science Applications International Corporation

Chantilly, VA • On-site

Full-time

Posted 28 days ago

SAIC rating

7.8

Company rating: 7.8 out of 10

Based on 78 frontline employees who took The Breakroom Quiz

71st of 204 rated it services

Job description

Job Description
SAIC has need for a Machine Learning Modeling and Simulation Engineer to support a rapidly expanding Government Intelligence Community (IC) customer with cutting-edge programs within the National Reconnaissance Office (NRO) in Chantilly, VA.
Note: The role offers a flexible work schedule, but we ask our team to be available for team meetings during core business hours (10:00 a.m. - 3:00 p.m.).
As the Machine Learning Modeling and Simulation Engineer, you will provide technical expertise across a variety of Machine Learning (ML) and Modeling and Simulation (M&S) topics, including developing and training ML models, designing simulation frameworks, conducting performance analyses, and applying data-driven approaches to solve complex problems. You will also assist with Systems Engineering topics (e.g., requirements, configuration management, readiness, verification and validation, etc.) to ensure seamless integration of ML capabilities within simulation environments.
Job Duties to include:
  • Develop and maintain physics-based simulation models of spacecraft systems, including structures, sensors, and mission environments.
  • Perform end-to-end performance modeling for satellite missions, integrating sensor, orbital, and environmental models.
  • Conduct sensor phenomenology studies, including optical, infrared, or radar modeling for detection, tracking, and signature analysis.
  • Perform orbital mechanics modeling including orbit determination, orbital maneuvering, and spacecraft flight dynamics.
  • Use scripting languages (Python, MATLAB, or similar) to automate workflows, perform data analysis, and interface between simulation tools.
  • Apply Artificial Intelligence/Machine Learning (AI/ML) techniques (e.g., supervised/unsupervised learning, reinforcement learning, predictive modeling) to enhance simulation fidelity and performance.
  • Develop AI/ML models to analyze and predict satellite system behaviors, performance metrics, and mission outcomes based on simulation data.
  • Design and implement algorithms for anomaly detection, predictive maintenance, and optimization of satellite operations.
  • Use statistical and machine learning techniques to analyze data, identify patterns, and uncover insights relevant to satellite systems.
  • Integrate AI/ML models into existing simulation frameworks and tools to enhance their capabilities.
  • Provide value-added judgment and offer strategic recommendations to the customer on program objectives, advanced technologies, and system enhancements.
  • Produce highly detailed, practical, and consistent deliverables that align with the organization's mission and objectives, with a focus on innovation and cutting-edge solutions in machine learning and simulation.

Qualifications
Required Education and Experience:
  • Bachelor's Aerospace Engineering, Mechanical Engineering, Physics, and five (5) years or more experience; Masters and three (3) years or more experience; PhD and 0 years related experience.
  • Active Top Secret/SCI w/Poly Clearance.
  • 3+ years of experience in modeling and simulation for aerospace or space systems.
  • Strong understanding of sensor phenomenology --such as optical, infrared, or radar systems --and associated modeling methods.
  • Intermediate Python programming experience, demonstrated through hands-on experience with tasks such as data manipulation, automation, and development of Python-based solutions. Experience with libraries such as NumPy, SciPy, pandas, and matplotlib is beneficial.
  • Ability to communicate technical results clearly in written and verbal formats.

About Us
SAIC® is a premier mission integrator focused on advancing the power of technology and innovation to serve and protect our world. Our robust portfolio of offerings across the defense, space, intelligence, and civilian markets includes secure high-end solutions in mission IT, enterprise IT, engineering services, and professional services. We integrate emerging technology, rapidly and securely, into mission critical operations that modernize and enable critical national imperatives.
We are approximately 23,000 strong; driven by mission, united by purpose, and inspired by opportunities. SAIC is an Equal Opportunity Employer. Headquartered in Reston, Virginia, SAIC has annual revenues of approximately $7.3 billion. For more information, visit saic.com. For ongoing news, please visit our newsroom.

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