ZipRecruiter

Log In

1

Physics Informed Machine Learning Jobs in Seattle, WA

Kindredventures

Machine Learning Engineer

Seattle, WA · On-site

$120K - $140K/yr

This is a requirement, a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning is required. We are currently not accepting applicants ...

Grid

Machine Learning Engineer

Seattle, WA

$120K - $140K/yr

This is a requirement, a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning is required. We are currently not accepting applicants ...

Grid

Machine Learning Engineer

Seattle, WA

$120K - $140K/yr

This is a requirement, a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning is required. We are currently not accepting applicants ...

Grid

Senior Machine Learning Engineer

Seattle, WA

$150K - $220K/yr

This is a requirement, a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning is required. We are currently not accepting applicants ...

Grid

Senior Machine Learning Engineer

Seattle, WA · On-site

$150K - $220K/yr

This is a requirement, a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning is required. We are currently not accepting applicants ...

next page

Showing results 1-20

All JobsPhysics Informed Machine Learning JobsPhysics Informed Machine Learning Jobs in Seattle, WA

Physics Informed Machine Learning information

See Seattle, WA salary details

$6

$22

$28

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

As of Sep 11, 2026, the average hourly pay for physics informed machine learning in Seattle, WA is $22.83, according to ZipRecruiter salary data. Most workers in this role earn between $14.23 and $28.99 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 Seattle, WA?

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

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

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

Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Seattle, WA as of September 2026, with employment types broken down into 88% Full Time, 6% Part Time, and 6% Contract. Highlights an 81% In-person, and 19% Remote job distribution, with an average salary of $47,491 per year, or $22.8 per hour.

Senior Quantum Applied Research Scientist, Calibration and Decoding

Redmond, WA • On-site

Nvidia Corporation
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidia Corporationexternal

$110K - $140K/yr

Full-time

Re-posted 6 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

Job description

At NVIDIA, we're solving the world's most exciting problems with our unique approach to accelerated computing. We're looking for a passionate scientist at the intersection of quantum device physics, quantum calibration, and machine learning. This role will path-find the future of intelligent, real-time models for fault-tolerant quantum hardware.
At NVIDIA, we want to help accelerate the entire quantum ecosystem. As a Sr. Quantum Applied Research Scientist, you will help design and build real-time models that learn from device physics, calibration experiments, decoding, and system performance. You will develop physics-informed data synthesis pipelines, post-trainable model architectures, and practical benchmarks that the quantum community can build on. Your research will translate qubit physics and the quantum control stack into performant AI systems for fault-tolerant quantum computing. The work will span synthetic training data generation, surrogate modeling, and co-optimized calibration-decoding pipelines. You will collaborate with teams across Product, Engineering, and Applied Research to push the frontier of Accelerated Quantum Supercomputers! Do you love developing new technology, enjoy working with people and teams around the world, and operating at the speed of light? If yes, we would love to hear from you!
What you'll be doing:
  • Research and develop open AI models for quantum system calibration to advance the state of the art and empower the quantum community to build on shared foundations.
  • Build physics-informed synthetic data generation pipelines that leverage quantum device models, noise channels, and Hamiltonian characterization to produce high-quality training data for upstream calibration and decoding model development.
  • Develop surrogate models of quantum hardware that capture device physics and drift behavior, enabling rapid performance prediction and parameter inference without full experimental overhead.
  • Architect performant real-time AI systems that jointly account for calibration state and decoding requirements, co-designing model latency, throughput, and update cadence to meet the demands of fault-tolerant feedback loops.
  • Apply reinforcement learning and online learning methods to calibration policy optimization, enabling models that improve continuously from hardware feedback and generalize across device families and modalities.
  • Develop GPU-accelerated implementations to ensure the full pipeline scales.
  • Communicate research findings and collaborate with academic and industry partners to advance the field, while championing rapid innovation, technical depth, and creative problem solving.

What we need to see:
  • Masters degree in Physics, Computer Science, Electrical Engineering, Applied Mathematics, or a related field (Ph.D. strongly preferred); or equivalent experience.
  • 8+ years of combined experience and high impact in quantum systems and AI/ML research.
  • Hands-on expertise in machine learning and deep learning for science or physics, including model architecture design, training at scale, fine-tuning, and evaluation.
  • Strong background in quantum device physics and information science, including noise models, error mechanisms, and fault-tolerant quantum systems across one or more qubit modalities.
  • Broad understanding of quantum control, such as pulse-level hardware interfaces and classical feedback through software abstractions.
  • Excellent communication and collaboration skills.

Ways to stand out from the crowd:
  • Hands-on experience developing learned calibration or decoding models and deploying them within real-time quantum control feedback loops, with direct awareness of latency and throughput constraints.
  • Deep expertise in reinforcement learning-including policy optimization, reward shaping, and sim-to-real transfer-applied to physical systems or closed-loop control problems.
  • Experience with physics-informed or generative approaches to synthetic data generation, including noise simulation, Hamiltonian learning, or data augmentation for scientific AI models.
  • Experience with large-scale model training and fine-tuning-including parameter-efficient methods (LoRA, QLoRA, adapters) and domain adaptation.
  • Proficiency with CUDA and NVIDIA GPU programming for accelerating quantum simulation, AI model training, or real-time inference workloads at scale.

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 192,000 USD - 304,750 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 12, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

View All Nvidia Jobs

Apply