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Physics Informed Machine Learning Jobs in Denver, CO

Cymertek Corporation

Data Scientist

Aurora, CO · On-site

$100 - $160/hr

... Machine Learning, Information Systems, Operations Research, Physics, Computational Biology, etc. ALTERNATE EXPERIENCEGeneral comment on degrees: Most contracts allow additional experience (4-5 years ...

Judge Group, Inc.

Astrodynamics Engineer

Westminster, CO · On-site

$120K - $180K/yr

Review machine-learning model results against orbital mechanics and physical expectations. * Provide physics-based inputs to concepts of operations and systems-engineering activities. * Evaluate ...

ICR, Inc.

Data Scientist - Aurora, CO

Aurora, CO · On-site

$100K - $210K/yr

Bachelors Degree in Mathematics, Physics, Statistics or related field. * Minimum five (5) years of ... Knowledge of supervised and unsupervised machine learning concepts, such as Artificial Neural ...

Cymertek

Data Scientist

Aurora, CO · On-site

... Machine Learning, Information Systems, Operations Research, Physics, Computational Biology, etc. ALTERNATE EXPERIENCE General comment on degrees: Most contracts allow additional experience (4-5 years ...

Pwc

AI Engineer

Denver, CO

$50K - $112K/yr

... informed decision-making and driving business growth. Within our Internal Firm Services practice ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

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

As of Aug 20, 2026, the average hourly pay for physics informed machine learning in Denver, CO is $20.65, according to ZipRecruiter salary data. Most workers in this role earn between $12.88 and $26.25 per hour, depending on experience, location, and employer.

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 Denver, CO?

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Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Denver, CO as of August 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $42,953 per year, or $20.7 per hour.

Field Site Senior ISR Engineer / Analyst - Colorado

Johns Hopkins Applied Physics Laboratory

Aurora, CO • On-site

Full-time

Re-posted 23 days ago

Johns Hopkins Applied Physics Laboratory rating

9.6

Company rating: 9.6 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

2nd of 74 rated research

Job description

Job Summary:
Johns Hopkins Applied Physics Laboratory (APL) is seeking a creative and expert engineer and/or quantitative analyst to lead and coordinate key elements of cross-organizational initiatives for the US military. The role involves leading technical development, coordinating with partners, and contributing to the development and testing of ISRT capabilities.
Responsibilities:
• Your primary responsibility will be to lead APL’s associated technical development and field test efforts, serving as APL’s technical liaison within a cross-organizational team consisting of industry and government partners and operators at an industry partner site in the Denver, Colorado area, at APL field sites and government sites in the Denver, Colorado area.
• You will coordinate and collaborate with other APL staff and across APL sites (Laurel, Denver and other remote locations) enabling operational implementations of software and capabilities directly with government and uniformed service members at fielded locations.
• You will contribute to teams developing, testing, and analyzing prototype software realizing new capabilities for ISRT applications.
• You will participate in field tests and experiments, including planning, execution, and data analysis.
• You will document and present results to managers, partners, sponsors, and technical workshops and conferences.
• You will travel to JHU APL in Laurel, MD as needed for project and program work, averaging about once per quarter, with flexibility required based on program needs.
Qualifications:
Required:
• Have a Bachelor’s degree in engineering, applied mathematics, computer science, physics, or another related field.
• Have at least seven years of relevant work experience in a related technical field.
• Have expertise in some of the following areas: systems engineering, statistical analysis, data fusion, signal and image processing, mathematical optimization, pattern recognition, machine learning, and artificial intelligence.
• Have skills and experience developing scientific and engineering applications in programming languages such as MATLAB, Python, C++, and Java and in Linux environments.
• Have strong inter-personal and written communications skills, experience leading teams and complex technical efforts, can work and collaborate effectively in a team environment.
• Have the ability to multi-task, support multiple, concurrent projects, and adapt to changing circumstances.
• Are willing and able to work full-time between two site locations in the Denver, Colorado area and travel occasionally to APL, government sites, and contractor facilities (local and non-local) primarily in secure, closed areas.
• Hold an active Top Secret security clearance and can ultimately obtain a TS/SCI+poly level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.
Preferred:
• Have a Master’s degree in engineering, applied mathematics, computer science, physics, or another related field.
• Have at least ten years of work experience in a relevant technical field.
• Have demonstrated experience with ISR processes, systems, platforms, and sensors used by the US military and intelligence community.
• Hold an active TS/SCI-level security clearance with a full-scope poly.
Company:
The Johns Hopkins Applied Physics Laboratory (APL) is a not-for-profit university-affiliated research center (UARC) that provides solutions to complex national security and scientific challenges with technical expertise and prototyping, research and development, and analysis. Founded in 1942, the company is headquartered in Laurel, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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