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Physics Informed Machine Learning Jobs in Bellevue, WA

Alignerr

Applied Physics

Seattle, WA · Remote

... physics-informed constraints * Document Failure Modes - Systematically record where and how AI ... No prior AI or machine learning experience required Nice to Have * Experience with data annotation ...

MORSE Corp

Machine Learning Engineer

Seattle, WA

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or ...

AZX

ML Engineer (Senior)

Seattle, WA · On-site

$140K - $220K/yr

Machine Learning Engineer (Senior) About AZX Our mission is to accelerate positive impact in critical industries through AI transformation. We specialize in physics-informed ML and enterprise AI ...

PitchBook

Machine Learning Engineer

Seattle, WA · On-site

... models are informed by high-quality data and support strategic product goals • Explore and ... machine learning engineering, with a strong focus on AI/ML applications in insight generation ...

PitchBook Data

Machine Learning Engineer

Seattle, WA · On-site

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role ... models are informed by high-quality data and support strategic product goals * Explore and ...

MORSE Corp

Machine Learning Engineer

Seattle, WA · On-site

$90K - $210K/yr

We are seeking a Machine Learning Engineer to join our team at MORSE. You will play a pivotal role ... D. in Computer Science, Computer Engineering, Data Science, Aerospace, Mathematics, Physics, or ...

Adobe

Senior Machine Learning Engineer

Seattle, WA

$172.50K - $306.63K/yr

A degree in computer science, statistics, operations research, applied physics, engineering, or a ... machine learning. Together, we'll develop groundbreaking solutions that empower creatives around ...

Axon

Principal Machine Learning Engineer

Seattle, WA · Hybrid

... new machine learning models and AI capabilities, leading to better and more responsible AI ... Bachelor's Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly ...

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

As of May 29, 2026, the average hourly pay for physics informed machine learning in Bellevue, WA is $22.64, according to ZipRecruiter salary data. Most workers in this role earn between $14.09 and $28.75 per hour, depending on experience, location, and employer.

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 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.
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Physics Informed Machine Learning jobs near you

Applied Physics

Alignerr

Seattle, WA • Remote

Full-time

Posted 20 days ago

Job description

Applied Physics - AI Data Trainer
About the Role
What if your deep expertise in physics could directly shape how AI understands the fundamental laws of the universe? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models - exposing gaps in their physical reasoning and helping ensure they never violate the principles of conservation of energy, momentum, or anything else your training tells you is non-negotiable.
This is a fully remote, flexible contract role built for researchers and scientists who want high-impact work on their own schedule. No prior AI experience required - just a command of physics that goes all the way down to first principles.
  • Organization
    : Alignerr
  • Type
    : Hourly Contract
  • Location
    : Remote
  • Commitment
    : 10-40 hours/week
    • What You'll Do
    • Design Advanced Physics Problems
      - Craft open-ended, multi-step problems at PhD qualifying exam level, spanning quantum mechanics, electrodynamics, thermodynamics, and classical mechanics
    • Author Gold-Standard Solutions
      - Write rigorous, step-by-step "golden responses" with flawless handling of physical constants, unit conversions, and mathematical derivations
    • Audit AI Reasoning
      - Evaluate AI-generated proofs and simulations for physical consistency, identifying where models hallucinate results or violate first principles
    • Refine Model Behavior
      - Provide structured, expert feedback that improves how AI handles boundary conditions, conservation laws, and physics-informed constraints
    • Document Failure Modes
      - Systematically record where and how AI reasoning breaks down so research teams can address root causes
      • Who You Are
      • Completed or nearly completed PhD in Applied Physics, Physics, Engineering Physics, or a closely related field
      • Deep mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
      • Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured English
      • Uncompromising precision with units, scientific notation, and the logical structure of proofs
      • Self-directed and reliable - comfortable working independently on technical tasks without hand-holding
      • No prior AI or machine learning experience required
      Nice to Have
      • Experience with data annotation, scientific dataset evaluation, or quality assurance workflows
      • Proficiency with tools like Python (NumPy/SciPy), MATLAB, or COMSOL
      • Background in research publication, technical writing, or academic instruction
      Why Join Us
      • Work on some of the most technically demanding AI projects in existence alongside world-leading research labs
      • Fully remote and asynchronous - work when and where it suits you
      • Freelance autonomy with the structure of meaningful, high-value technical work
      • Rare opportunity to apply your physics expertise beyond academia in a high-impact, forward-looking field
      • Potential for ongoing work and contract extension as new projects launch

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