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Physics Informed Machine Learning Jobs in Bellingham, WA

Physics Informed Machine Learning information

See Bellingham, WA salary details

$5

$20

$26

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

As of Jun 20, 2026, the average hourly pay for physics informed machine learning in Bellingham, WA is $20.85, according to ZipRecruiter salary data. Most workers in this role earn between $12.98 and $26.49 per hour, depending on experience, location, and employer.

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.

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 job categories do people searching Physics Informed Machine Learning jobs in Bellingham, WA look for? The top searched job categories for Physics Informed Machine Learning jobs in Bellingham, WA are:
What cities near Bellingham, WA are hiring for Physics Informed Machine Learning jobs? Cities near Bellingham, WA with the most Physics Informed Machine Learning job openings:
Data Scientist- RF/Acoustics Signal Processing

Data Scientist- RF/Acoustics Signal Processing

Cutsforth, LLC

Ferndale, WA • Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago


Job description

Role Information:
  • Job Title: Data Scientist — RF/Acoustics Signal Processing
  • Work Location: Fully remote position, home office- can NOT be located in NY, CA or IL
  • Employment Type: Full-time
  • Employment Status: Exempt, salaried
  • Visa sponsorship is not available for this position.
  • Must reside in the United States.
  • We are not accepting applicants for remote workers in California, Illinois, and New York at this time.
Alignment with Corporate Values:All Cutsforth employees are expected to perform their work in a manner that exhibits understanding and adherence to the Company Mission and Core Attributes of Cutsforth Employees. Employees in management roles must exhibit continual improvement along Cutsforth’s Leadership Traits. Further, each employee must read and adhere to corporate policies and safety protocols.
  • Learn more about Cutsforth here: Cutsforth.com/About
  • Read our Mission & Values here: Cutsforth.com/Values
Compensation:
  • $98,837 - $154,546, depending on years of experience
Role Overview:Applies data science and machine learning to the analysis of radio frequency and acoustic signals, transforming raw time-series sensor data into actionable diagnostics and predictive insights. Partners with engineering and domain experts to design and deploy production-grade signal processing and ML solutions across industrial, communications, and defense-adjacent applications. Operates effectively in ambiguous problem spaces where signal quality, environmental noise, and domain constraints require both technical rigor and adaptive thinking.
Key Responsibilities:
  • Design and develop signal processing pipelines and machine learning models that operate on RF, acoustic, and time-series sensor data, including beamforming, BSS, spectral subtraction, matched filtering, wavelet decomposition, and time-frequency analysis techniques.
  • Evaluate algorithm performance using both objective metrics and subjective measures, including integration with speech recognition engines where applicable.
  • Perform exploratory data analysis, feature engineering, and signal feature extraction on raw demodulated RF and acoustic data to surface patterns and anomalies.
  • Analyze and interpret signals from various electrical asset monitoring systems utilizing RF, acoustic, and signal processing expertise to support fault isolation and anomaly detection.
  • Use asset monitoring sensor data as measurement to characterize and validate signal data.
  • Apply data-driven signal processing methods to characterize and isolate faults at the subsystem, component, and LRU level — identifying root causes from spectral, RF, and acoustic sensor data in complex industrial systems.
  • Contribute to end-to-end ML workflows including data ingestion, model training, inference, and monitoring for drift and degradation in live environments.
  • Collaborate with engineering, product, and domain SMEs to translate operational challenges into well-scoped data science solutions.
  • Communicate findings, model performance, and business value clearly through visualizations, written documentation, and presentations to technical and non-technical stakeholders.
  • Explore and evaluate emerging signal processing and AI techniques, recommending production incorporation where appropriate.
Required Qualifications:
  • Bachelor’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Aerospace Engineering, or a closely related engineering discipline required.
  • 5+ years of professional experience in data science, machine learning, or applied signal processing, with demonstrated work on RF, acoustic, ultrasonic, or communications signal data.
  • Direct industry experience in one or more of: Aerospace, Telecommunications, Military/Defense communications, Industrial Acoustics, or RF/Electronic Systems.
  • Hands-on experience with time-series and signal processing techniques, including spectral analysis, filtering, and feature extraction from raw sensor or radio data.
  • Proficiency in Python, including scientific computing libraries (NumPy, SciPy, pandas) and ML frameworks (scikit-learn, PyTorch, or TensorFlow).
  • Demonstrated use of RF measurement and analysis workflows, including use of spectrum analyzers, network analyzers, signal generators, and oscilloscopes in a professional engineering context.
  • Strong analytical and problem-solving skills with the capacity to work through ambiguous or data-sparse problem spaces.
  • Excellent written and verbal communication skills; ability to present technical findings to non-technical audiences.
  • Knowledge of Electromagnetic Compliance techniques.
Preferred Qualifications:
  • Master’s degree in Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Acoustical Engineering, Aerospace Engineering, Data Science, or a related field.
  • Experience with radar sensing, sonar, guided-wave radar, ultrasonic sensing, or capacitive sensing systems.
  • Experience working with wireless protocols (4G/LTE, 5G, or military-equivalent).
  • Demonstrated ability to own an ML model from prototype through production, including monitoring and retraining.
  • Familiarity with beamforming, spatial filtering, or array signal processing in acoustic or RF environments.
  • Background in military communications systems, avionics radar, or cellular infrastructure signal analysis.
  • Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps tooling (MLflow, Docker, Airflow, CI/CD pipelines).
  • Experience with multimodal data fusion, edge ML deployment, or physics-informed modeling approaches.
  • Active participation in the broader signal processing or data science community through publications, open-source projects, or conference presentations.
  • Amateur (Ham) Radio license or comparable hands-on RF communications background.
Other Qualifications:
  • Successfully pass background check for cybersecurity site access.
  • Strong foundation in signal processing theory and application, including experience with RF, acoustic, or time-series data in a professional setting.
  • Proficiency in Python for data manipulation, signal processing, and model development (NumPy, SciPy, pandas, scikit-learn, PyTorch or TensorFlow).
  • Ability to work with uncertainty and incomplete information — comfortable forming and testing hypotheses when ground truth is limited.
  • Clear communicator capable of translating technical signal processing and ML findings to non-specialist audiences.
  • Self-directed and effective working remotely across cross-functional teams.
  • Must reside in the United States; not accepting applicants in California, Illinois, or New York.
Cybersecurity Role Expectations:
  • Candidate will be responsible for reviewing policies and procedures related to cybersecurity and those relevant to the functions of their role.
  • Candidate is expected to maintain a cybersecure work environment.
Benefits:
  • Paid Time Off
  • Medical, Vision, Dental Insurance
  • Health Savings Account with Employer contributions
  • 401(k) with Employer match
  • Short-term & Long-term Disability Coverage
  • Accidental Death & Dismemberment Coverage
  • Life Insurance Coverage
  • Eight paid holidays per year
  • All other benefits required by applicable law

 

Alignment with Corporate Values

All Cutsforth employees are expected to perform their work in a manner that exhibits understanding and adherence to the Company Mission and Core Attributes of Cutsforth Employees. Employees in management roles must exhibit continual improvement along Cutsforth’s Leadership Traits. Further, each employee must read and adhere to corporate policies and safety protocols.

  • Learn more about Cutsforth here: Cutsforth.com/About
  • Read our Mission & Values here: Cutsforth.com/Values

Equal Employment Opportunity Statement:

Cutsforth will not discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, or national origin. Cutsforth will take affirmative action to ensure that applicants are employed, and that employees are treated during employment, without regard to their race, color, religion, sex, sexual orientation, gender identity, or national origin. Such action shall include, but not be limited to the following: Employment, upgrading, demotion, or transfer, recruitment or recruitment advertising; layoff or termination; rates of pay or other forms of compensation; and selection for training, including apprenticeship. Cutsforth agrees to post in conspicuous places, available to employees and applicants for employment, notices to be provided by the provisions of this nondiscrimination clause.

For Cutsforth's full Equal Employment Opportunity Policy, click here: EEO Notice to Employees & Applicants

California Privacy Notice:
If you are a California resident, please review our California Job Applicant Privacy Policy for details regarding the personal information we collect during the hiring process, how we use it, and your rights under the CCPA. By submitting your application, you acknowledge that you have read and understand our privacy practices.
For Cutsforth's full CCPA Privacy Policy, click here CCPA: California Privacy Notice to Applicants

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