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Physics Informed Machine Learning Jobs in Bellevue, WA

Sr. Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

  • Medical

  • Life

  • Retirement

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

Responsibilities : • Develop and validate machine-learning frameworks for FRC plasma-dynamics, leveraging physics-grounded ML approaches (e.g., differentiable physics, PINNs, surrogate modeling, or ...

Senior Machine Learning Engineer II

Seattle, WA · On-site +1

$118K - $163K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Your Impact We are seeking a seasoned Machine Learning Engineer to join a new team building agentic ... Bachelor's Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly ...

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Physics Informed Machine Learning information

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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 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?

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 Bellevue, WA?

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

What job categories do people searching Physics Informed Machine Learning jobs in Bellevue, WA look for?

The top searched job categories for Physics Informed Machine Learning jobs in Bellevue, WA are:

What cities near Bellevue, WA are hiring for Physics Informed Machine Learning jobs?

Cities near Bellevue, WA with the most Physics Informed Machine Learning job openings:

Infographic showing various Physics Informed Machine Learning job openings in Bellevue, WA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 1% Temporary, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $47,099 per year, or $22.6 per hour.

Machine Learning Engineer - Special Projects

Apple Inc.

Seattle, WA • On-site

$150.40 - $277.60/hr

Other

Medical, Dental, Retirement

Posted 2 days ago

New


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Santa Clara, California, United States Machine Learning and AI

We're seeking research engineers to build infrastructure for breakthrough innovations in AI agents, reinforcement learning, and simulation environments. You will design and implement high-quality data pipelines, simulation systems, and tooling that enable cutting‑edge agent research. You will work in an organization of world‑class machine learning researchers and engineers. Our work powers technologies across the Apple ecosystem and is published in the most selective scientific journals and conferences.

Description

We are a team of best‑in‑the‑world research scientists and engineers building the foundations for autonomous AI systems. We work on exciting new technologies that bring joy to millions of people. In our daily work, the team stays innovative, productive, and fun by sharing some key values:

Responsibilities
  • Passion for the mission: We're here to make something extraordinary. We seek whatever work is right and strive for the best possible results.
  • Modesty: The right answer is more significant than being right. We search for solutions as a team and value clear‑eyed feedback.
  • Lean habits: You can't grow without limits. Time constraints and big goals encourage us to sharpen our focus and learn to make phenomenal decisions.
Minimum Qualifications
  • 5+ years of ML engineering experience building and maintaining data‑intensive systems – including feature pipelines, training infrastructure, model serving, or evaluation frameworks.
  • Solid software engineering skills in complex systems – fluency in Python. You deliver clean, well‑tested code.
  • Hands‑on experience with distributed ML systems – CI/CD at scale, distributed testing, or ML evaluation pipelines.
  • Strong quantitative and data skills – comfortable with SQL, statistical reasoning, and translating ambiguous signals into clear, actionable findings.
  • Proven track record shipping ML systems end‑to‑end – from problem framing and data curation through training, evaluation, deployment, and monitoring in production.
Preferred Qualifications
  • Bachelors or Masters Degree in Computer Science, Engineering, Math, or Physics from a strong program.
  • 2+ years at a company building AI products or agent systems.
  • Experience with job orchestration frameworks (Airflow, Prefect, Ray, etc.).
  • Familiarity with macOS/iOS development ecosystems.
  • Active personal interest in AI agents—you're already experimenting on your own time.

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace.

Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976