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Physics Informed Machine Learning Jobs in Irvine, CA

Rivian

Durability Analytics Engineer

Irvine, CA · On-site

$96K - $120K/yr

Develop and validate machine learning models to estimate vehicle loads, drive events, fatigue ... A good understanding of vehicle physics and automotive engineering, is preferred. * Passion for ...

Rivian

Durability Analytics Engineer

Irvine, CA · On-site

$96K - $120K/yr

Develop and validate machine learning models to estimate vehicle loads, drive events, fatigue ... A good understanding of vehicle physics and automotive engineering, is preferred. * Passion for ...

Rivian

Durability Analytics Engineer

Irvine, CA · On-site

$96K - $120K/yr

Develop and validate machine learning models to estimate vehicle loads, drive events, fatigue ... A good understanding of vehicle physics and automotive engineering, is preferred. * Passion for ...

TRL11, Inc.

Sr Algorithms/Video Engineer

Irvine, CA · On-site

$150K - $220K/yr

... Physics or related field. * Minimum of 3 years of industry experience in developing and implementing machine learning and computer vision algorithms and workflows. * Strong programming skills in C/C ...

TRL11, Inc.

Sr Algorithms/Video Engineer

Irvine, CA · On-site

$150K - $220K/yr

... Physics or related field. * Minimum of 3 years of industry experience in developing and implementing machine learning and computer vision algorithms and workflows. * Strong programming skills in C/C ...

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

As of Aug 24, 2026, the average hourly pay for physics informed machine learning in Irvine, CA is $21.54, according to ZipRecruiter salary data. Most workers in this role earn between $13.41 and $27.36 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.

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Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Irvine, CA as of August 2026, with employment types broken down into 87% Full Time, and 13% Part Time. Highlights an 100% In-person job distribution, with an average salary of $44,794 per year, or $21.5 per hour.

Senior Machine Learning Engineer II

Long Beach, CA • On-site

Rocket Lab Corporation
Aerospace Product and Parts Manufacturing • 201 - 500 employees

9.2

Company rating: 9.2 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

4th of 72 rated aerospace companies

People enjoy working here

Good employer

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Learn more about Rocket Lab Corporationexternal

$128K - $169K/yr

Full-time

Posted 3 days ago

New

Job description

SPACE SYSTEMS

At Rocket Lab, we're not just launching rockets - we're building the future of space. Our Space Systems team builds everything from complete spacecraft, precision payloads to the components and subsystems that allow them to thrive in space, like solar panels, flight software, star trackers, optical systems, separation systems, radios, and more.

Our Space Systems team has enabled more than 1,700 missions, ranging from interplanetary exploration, in-space manufacturing to national security and defense initiatives. The team has built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Development Agency, and the U.S. Space Force. Whether it's a single high-performance spacecraft, constellation, or the vertically integrated components that help them get to space - our world class Space Systems team is empowering some of the boldest and most ambitious space missions.

SENIOR MACHINE LEARNING ENGINEER II

Rocket Lab's Optical Systems division solves mission-critical space domain and Intelligence, Surveillance, and Reconnaissance (ISR) challenges for Department of Defense (DoD) and Intelligence Community (IC) customers. Our vision is to revolutionize the space-based payload market with innovative and novel designs for space, terrestrial, and airborne environments. Building on more than 20 years of electro-optical and infrared systems innovation, Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.

As a Senior Machine Learning Engineer II based at our Optical Systems sites in Long Beach, CA, you will have the opportunity to support Tranche 3 of the U.S. Space Development Agency's (SDA) Proliferated Warfighter Space Architecture (PWSA) and beyond by building deep learning neural networks for advanced Electro-Optical (EO/IR) image processing.

WHAT YOU'LL DO

  • Contribute your experience to developing solutions for real-world problems.
  • Design, train, and deploy machine learning models for Optical Systems applications
  • Build and maintain ML pipelines for data ingestion, feature engineering, training, and inference.
  • Collaborate with other researchers/engineers on artificial intelligence, machine learning, and computer vision.
  • Preform rapid prototyping and enhanced development to be integrated into operational systems.
  • Perform troubleshooting, bug fixes, and maintenance of existing and new systems.
  • Stay current with ML research and evaluate new tools, frameworks, and techniques

 WHAT WE'RE LOOKING FOR IN A SENIOR MACHINE LEARNING ENGINEER II:

  • Bachelor's degree and 8+ years of experience, master's degree and 6+ years of experience, or a Ph.D. in Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Physics, or related field
  • Strong background in machine learning including model selection, architecting, training, validation, testing, and deployment
  • Experience in building deep learning neural network for computer vision, image processing, or video analysis (e.g., object detection, image segmentation, and tracking)
  • Strong math background, particularly linear algebra
  • Proficiency in Python
  • Experience with deep learning libraries (Keras, TensorFlow, Pytorch, etc)
  • Software engineering fundamentals: version control, testing, CI/CD, containerization
  • U.S. citizenship is required, due to program requirements
  • Ability to obtain and maintain an U.S. Government Security Clearance

NICE TO HAVE: 

  • Proficiency in C/C++/Rust
  • Experience curating quality, real-world datasets for training deep learning models
  • TS/SCI security clearance

This position may require prolonged periods of sitting, standing, walking, computer work, and occasional exposure to moderate levels of noise, dust, and fumes in production areas.

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