Acoustic Data Science Engineer (Probes) / Ingénieur en Data Science Acoustique (Probes)

Job Description Summary

Working within GE Healthcare’s Global Ultrasound Probes business, the role focuses on applying machine learning methods to ultrasound transducer design, development, and manufacturing. The successful candidate will use their technical background to advance projects that improve design and manufacturing efficiency and implement predictive performance monitoring to assess the state‑of‑health of deployed transducers.

Roles and Responsibilities

• Define high‑level project/product requirements for new and existing ML products and projects.
• Define user and customer requirements in collaboration with global sites and project stakeholders.
• Propose short, mid, and long‑term vision, maintain schedule, and build a roadmap.
• Delegate technical tasks to junior team members.

Desired Technical Experience

• Ultrasound experience:
  • Experience in acoustics or ultrasound measurements and processing.
  • Experience in transducer design, development, testing, or modeling.
  • Background in ultrasonic nondestructive testing.
  • Experience testing and analyzing figures of merit on ultrasound devices.
• Machine & Deep Learning Experience:
  • Strong understanding of supervised, unsupervised, and deep learning methods.
  • Experience developing and deploying models for signal‑processing tasks such as classification, feature extraction, and predictive modeling for physical systems.
  • Practical knowledge of model evaluation, validation strategies, cross‑validation, bias/variance tradeoffs, and hyperparameter tuning.
  • Ability to read and implement methods from current ML research literature.
  • Experience applying ML methods to physical systems, transducers, or hardware‑related performance modeling.
  • Familiarity with simulation‑based training (e.g., generating synthetic waveform data for model robustness).
  • Familiarity with deep learning (e.g., convolutional and recurrent neural networks).
• Cloud Experience:
  • Understanding code deployment on cloud environments with pipelines.
  • Understanding cloud architecture and key steps of data flow (data acquisition, processing, storage and visualization).
  • Experience developing visualization tools for different user groups and focus areas.
  • Familiarity with cloud services.
• Tool Experience:
  • MATLAB
  • Python (and libraries NumPy, SciPy, PyTorch, etc.)
  • Microsoft Visual Studio Code
  • GitHub Copilot
  • Microsoft Power BI
  • SQL
  • Git or GitLab
  • Cloud‑based pipelines like Azure ML, AWS SageMaker, or similar.

Required Qualifications

• University degree in engineering, acoustics, physics, or applied mathematics.
• Master’s or Ph.D. preferred.

Desired Characteristics

• Strong oral and written communication skills.
• Ability to work effectively both autonomously and in distributed, global teams.
• Demonstrated ability to analyze and resolve problems.

Additional Information

• Relocation Assistance Provided: No