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Physics Informed Machine Learning Jobs in Washington

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 ...

STR

Senior Machine Learning Engineer

Arlington, VA · On-site

$155K - $195K/yr

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Physics, or a related technical field * 6+ years of professional software engineering and/or ...

STR

Senior Machine Learning Engineer

Washington, DC · On-site

$155K - $195K/yr

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Physics, or a related technical field * 6+ years of professional software engineering and/or ...

STR

Senior Machine Learning Engineer

Arlington, VA · On-site

$155K - $195K/yr

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Physics, or a related technical field * 6+ years of professional software engineering and/or ...

STR

Senior Machine Learning Engineer

Arlington, VA · On-site

$155K - $195K/yr

The Role As a Senior Machine Learning Engineer, you will turn cutting-edge AI/ML research into ... Physics, or a related technical field * 6+ years of professional software engineering and/or ...

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Physics Informed Machine Learning information

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.

What are popular job titles related to Physics Informed Machine Learning jobs in Washington?

For Physics Informed Machine Learning jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in Washington look for?

The top searched job categories for Physics Informed Machine Learning jobs in Washington are:

What cities in Washington are hiring for Physics Informed Machine Learning jobs?

Cities in Washington with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Washington as of August 2026, with employment types broken down into 6% Internship, 42% Full Time, 41% Part Time, and 11% Contract. Highlights an 100% In-person job distribution.

Machine Learning Engineer- Senior

SOSi

Chantilly, VA • On-site

$125K - $165K/yr

Full-time

Re-posted 2 days ago

Job description

Company Description
Founded in 1989, SOSi is among the largest private, founder-owned technology and services integrators in the defense and government services industry. We deliver tailored solutions, tested leadership, and trusted results to enable national security missions worldwide.
Job Description
Overview
SOSi is seeking a skilled Machine Learning Engineer to support a US government customer in Chantilly, VA. In this job you will work with other talented data scientists, software developers, and SMEs to apply the best practices and state of the art data science and machine learning processes. This role requires the ability to solve complex problems independently and collaboratively in a dynamic work environment. Strong communication skills are essential for translating technical concepts to non-technical stakeholders and delivering actionable insights.
Essential Job Duties
  • Leverage data science and machine learning processes to answer mission challenges.
  • Develop and iterate rapid prototype solutions, leveraging open-source models and technologies where possible
  • Flexibility to support topics such as object detection, data triage, search/optimization, image/video analysis, facial recognition, behavior detection, and automated discovery.
  • Apply excellent problem-solving skills to address technical challenges, both independently and as part of a team in a fast-paced environment.
  • Comprehend project requirements and execute tasks accordingly, ensuring alignment with project goals and timelines.
  • Effectively communicate technical concepts and deliver results to non-technical leadership and stakeholders, facilitating informed decision-making.

Qualifications
Minimum Requirements
  • Existing TS/SCI (with poly). This security clearance requires U.S. citizenship. Candidates will not be nominated for new clearances.
  • Minimum 5 years of experience in a data science/engineer role.
  • Experience developing and using agentic AI frameworks including Autogen.
  • Experience with prompt engineering beyond traditional code writing and debugging. Understanding of how to craft prompts for discrete tasks such as data labeling and processing.
  • Experience with asynchronous Python development using frameworks like Ray and FastAPI.
  • Experience developing and deploying AI/ML models as part of production systems, implementing software development best practices for scalability and reliability.
  • Experience developing and applying advanced machine learning methods including clustering, regression, optimization, recommender engines, and artificial neural networks.
  • Deploying models into multi-node Ray clusters utilizing various GPU resources.
  • Experience with developing and deploying resources to cloud environments.
  • Experience working in Linux and Windows environments and managing resources for efficiency.
  • Demonstrated ETL expertise.

Preferred Qualifications
  • Bachelor's degree in Data Science, Statistics, Computer Science, or a related field; OR equivalent experience.
  • Experience in the US Intelligence Community.

Additional Information
Work Environment
  • Office setting with a combination of desk work and meetings.

Working at SOSi
All interested individuals will receive consideration and will not be discriminated against for any reason.

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